Journal Cover
Future Internet
Journal Prestige (SJR): 0.219
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  This is an Open Access Journal Open Access journal
ISSN (Print) 1999-5903
Published by MDPI Homepage  [222 journals]
  • Future Internet, Vol. 11, Pages 182: An Ontology-Based Recommender System
           with an Application to the Star Trek Television Franchise

    • Authors: Paul Sheridan, Mikael Onsjö, Claudia Becerra, Sergio Jimenez, George Dueñas
      First page: 182
      Abstract: Collaborative filtering based recommender systems have proven to be extremely successful in settings where user preference data on items is abundant. However, collaborative filtering algorithms are hindered by their weakness against the item cold-start problem and general lack of interpretability. Ontology-based recommender systems exploit hierarchical organizations of users and items to enhance browsing, recommendation, and profile construction. While ontology-based approaches address the shortcomings of their collaborative filtering counterparts, ontological organizations of items can be difficult to obtain for items that mostly belong to the same category (e.g., television series episodes). In this paper, we present an ontology-based recommender system that integrates the knowledge represented in a large ontology of literary themes to produce fiction content recommendations. The main novelty of this work is an ontology-based method for computing similarities between items and its integration with the classical Item-KNN (K-nearest neighbors) algorithm. As a study case, we evaluated the proposed method against other approaches by performing the classical rating prediction task on a collection of Star Trek television series episodes in an item cold-start scenario. This transverse evaluation provides insights into the utility of different information resources and methods for the initial stages of recommender system development. We found our proposed method to be a convenient alternative to collaborative filtering approaches for collections of mostly similar items, particularly when other content-based approaches are not applicable or otherwise unavailable. Aside from the new methods, this paper contributes a testbed for future research and an online framework to collaboratively extend the ontology of literary themes to cover other narrative content.
      Citation: Future Internet
      PubDate: 2019-08-22
      DOI: 10.3390/fi11090182
      Issue No: Vol. 11, No. 9 (2019)
  • Future Internet, Vol. 11, Pages 183: A Proof-of-Concept Demonstration of
           Isolated and Encrypted Service Function Chains

    • Authors: Håkon Gunleifsen, Thomas Kemmerich, Vasileios Gkioulos
      First page: 183
      Abstract: Contemporary Service Function Chaining (SFC), and the requirements arising from privacy concerns, call for the increasing integration of security features such as encryption and isolation across Network Function Virtualisation (NFV) domains. Therefore, suitable adaptations of automation and encryption concepts for the development of interconnected data centre infrastructures are essential. Nevertheless, packet isolation constraints related to the current NFV infrastructure and SFC protocols, render current NFV standards insecure. Accordingly, the goal of our work was an experimental demonstration of a new SFC packet forwarding standard that enables contemporary data centres to overcome these constraints. This article presents a comprehensive view of the developed architecture, focusing on the elements that constitute a new forwarding standard of encrypted SFC packets. Through a Proof-of-Concept demonstration, we present our closing experimental results of how the architecture fulfils the requirements defined in our use case.
      Citation: Future Internet
      PubDate: 2019-08-24
      DOI: 10.3390/fi11090183
      Issue No: Vol. 11, No. 9 (2019)
  • Future Internet, Vol. 11, Pages 184: Mobility-Enabled Edge Server
           Selection for Multi-User Composite Services

    • Authors: Wenming Zhang, Yiwen Zhang, Qilin Wu, Kai Peng
      First page: 184
      Abstract: In mobile edge computing, a set of edge servers is geographically deployed near the mobile users such that accessible computing capacities and services can be provided to users with low latency. Due to user’s mobility, one fundamental and critical problem in mobile edge computing is how to select edge servers for many mobile users so that the total waiting time is minimized. In this paper, we propose a multi-user waiting time computation model about composite services and show the resource contention of the edge server among mobile users. Then, we introduce a novel and optimal Multi-user Edge server Selection method based on Particle swarm optimization (MESP) in mobile edge computing, which selects edge servers for mobile uses in advance within polynomial time. Extensive simulations on a real-world data-trace show that the MESP algorithm can effectively reduce the total waiting time compared with traditional approaches.
      Citation: Future Internet
      PubDate: 2019-08-25
      DOI: 10.3390/fi11090184
      Issue No: Vol. 11, No. 9 (2019)
  • Future Internet, Vol. 11, Pages 185: An Improved Method for Named Entity
           Recognition and Its Application to CEMR

    • Authors: Ming Gao, Qifeng Xiao, Shaochun Wu, Kun Deng
      First page: 185
      Abstract: Named Entity Recognition (NER) on Clinical Electronic Medical Records (CEMR) is a fundamental step in extracting disease knowledge by identifying specific entity terms such as diseases, symptoms, etc. However, the state-of-the-art NER methods based on Long Short-Term Memory (LSTM) fail to exploit GPU parallelism fully under the massive medical records. Although a novel NER method based on Iterated Dilated CNNs (ID-CNNs) can accelerate network computing, it tends to ignore the word-order feature and semantic information of the current word. In order to enhance the performance of ID-CNNs-based models on NER tasks, an attention-based ID-CNNs-CRF model, which combines the word-order feature and local context, is proposed. Firstly, position embedding is utilized to fuse word-order information. Secondly, the ID-CNNs architecture is used to extract global semantic information rapidly. Simultaneously, the attention mechanism is employed to pay attention to the local context. Finally, we apply the CRF to obtain the optimal tag sequence. Experiments conducted on two CEMR datasets show that our model outperforms traditional ones. The F1-scores of 94.55% and 91.17% are obtained respectively on these two datasets, and both are better than LSTM-based models.
      Citation: Future Internet
      PubDate: 2019-08-26
      DOI: 10.3390/fi11090185
      Issue No: Vol. 11, No. 9 (2019)
  • Future Internet, Vol. 11, Pages 186: Sustainable Communication Systems: A
           Graph-Labeling Approach for Cellular Frequency Allocation in
           Densely-Populated Areas

    • Authors: Adebola Orogun, Oluwaseun Fadeyi, Ondrej Krejcar
      First page: 186
      Abstract: The need for smart and sustainable communication systems has led to the development of mobile communication networks. In turn, the vast functionalities of the global system of mobile communication (GSM) have resulted in a growing number of subscribers. As the number of users increases, the need for efficient and effective planning of the “limited” frequency spectrum of the GSM is inevitable, particularly in densely-populated areas. As such, there are ongoing discussions about frequency (channel) allocation methods to resolve the challenges of channel allocation, which is a complete NP (Nondeterministic Polynomial time) problem. In this paper, we propose an algorithm for channel allocation which takes into account soft constraints (co-channel interference and adjacent channel interference). By using the Manhattan distance concept, this study shows that the formulation of the algorithm is correct and in line with results in the literature. Hence, the Manhattan distance concept may be useful in other scheduling and optimization problems. Furthermore, this unique concept makes it possible to develop a more sustainable telecommunication system with ease of connectivity among users, even when several subscribers are on a common frequency.
      Citation: Future Internet
      PubDate: 2019-08-26
      DOI: 10.3390/fi11090186
      Issue No: Vol. 11, No. 9 (2019)
  • Future Internet, Vol. 11, Pages 187: Research on SWIM Services Dynamic
           Migration Method

    • Authors: Zhijun Wu, Shengyan Zhou, Liang Liu, Jin Lei
      First page: 187
      Abstract: Air traffic management (ATM) plays an important role in maintaining and promoting air traffic safety, maintaining air traffic order and ensuring smooth air traffic. As the core of air traffic management, it is essential to ensure the safe and stable operation of system-wide information management (SWIM). Facing the complex and ever-changing network environment, a SWIM services dynamic migration method is proposed in this paper. This method combines SWIM core services to select destination nodes and migrate services. The experiment proves that the method can hide the service node while ensuring service continuity and increase the difficulty of malicious detection. By comparing with others, this method is more suitable for SWIM in terms of invulnerability. The throughput and delay performance of the method can meet the needs of SWIM.
      Citation: Future Internet
      PubDate: 2019-08-27
      DOI: 10.3390/fi11090187
      Issue No: Vol. 11, No. 9 (2019)
  • Future Internet, Vol. 11, Pages 188: SEO Practices: A Study about the Way
           News Websites Allow the Users to Comment on Their News Articles

    • Authors: Minos-Athanasios Karyotakis, Evangelos Lamprou, Matina Kiourexidou, Nikos Antonopoulos
      First page: 188
      Abstract: In the current media world, there is a huge debate about the importance of the visibility of a news website in order to secure its existence. Thus, search engine optimization (SEO) practices have emerged in the news media systems around the world. This study aimed to expand the current literature about the SEO practices by focusing on examining, via the walkthrough method, the ways that news companies allow the users to comment on their online news articles. The comments on the news websites are related to the notions of social influence, information diffusion, and play an essential role as a SEO practice, for instance, by providing content and engagement. The examined sample was collected by the most visited news websites’ rankings of for a global scale and for the countries Greece and Cyprus. The findings reveal that the news websites throughout the globe use similar features and ways to support the comments of the users. In the meantime, though, a high number of the news websites did not allow the users to use their social media accounts in order to comment the provided news articles, or provided multiple comment platforms. This trend goes against the SEO practices. It is believed that this finding is associated with the difficulty of the news organizations to regulate and protect themselves by the users’ comments that promote, in some case harmful rhetoric and polarization.
      Citation: Future Internet
      PubDate: 2019-08-30
      DOI: 10.3390/fi11090188
      Issue No: Vol. 11, No. 9 (2019)
  • Future Internet, Vol. 11, Pages 189: RFID Based Embedded System for
           Sustainable Food Management in an IoT Network Paradigm

    • Authors: Raúl Parada, Alfonso Palazón, Carlos Monzo, Joan Melià-Seguí
      First page: 189
      Abstract: A third of the food produced in the world ends up in the rubbish, enough to put an end to world hunger. On the other hand, society is increasingly concerned to bring healthy eating habits. A RFID (radio frequency identification) food management system is designed to palliate the previously described issues in an Internet of Things (IoT) network paradigm. It consists of RFID readers placed on a user’s kitchen furniture, which automatically reads food information. There is no need for direct sight between reader and tag, as it occurs through the barcode technology. As a complement, a multi-platform web application is developed, allowing its users to check the date of food expiration and other detailed information. The application notifies the user when a product is about to expire. It also offers recipes that might be prepared with available foods, thus preventing them from being wasted. The recipes are accompanied by their nutritional information, so that the user can exhaustively monitor what he/she eats. This embedded system may provide economic benefits to the manufacturer, since it allows supermarkets to pay for displaying their products advertised through the application. After system deployment, design conclusions are shown, and future improvement points are indicated.
      Citation: Future Internet
      PubDate: 2019-09-01
      DOI: 10.3390/fi11090189
      Issue No: Vol. 11, No. 9 (2019)
  • Future Internet, Vol. 11, Pages 190: Deep Learning-Based Sentimental
           Analysis for Large-Scale Imbalanced Twitter Data

    • Authors: Nasir Jamal, Chen Xianqiao, Hamza Aldabbas
      First page: 190
      Abstract: Emotions detection in social media is very effective to measure the mood of people about a specific topic, news, or product. It has a wide range of applications, including identifying psychological conditions such as anxiety or depression in users. However, it is a challenging task to distinguish useful emotions’ features from a large corpus of text because emotions are subjective, with limited fuzzy boundaries that may be expressed in different terminologies and perceptions. To tackle this issue, this paper presents a hybrid approach of deep learning based on TensorFlow with Keras for emotions detection on a large scale of imbalanced tweets’ data. First, preprocessing steps are used to get useful features from raw tweets without noisy data. Second, the entropy weighting method is used to compute the importance of each feature. Third, class balancer is applied to balance each class. Fourth, Principal Component Analysis (PCA) is applied to transform high correlated features into normalized forms. Finally, the TensorFlow based deep learning with Keras algorithm is proposed to predict high-quality features for emotions classification. The proposed methodology is analyzed on a dataset of 1,600,000 tweets collected from the website ‘kaggle’. Comparison is made of the proposed approach with other state of the art techniques on different training ratios. It is proved that the proposed approach outperformed among other techniques.
      Citation: Future Internet
      PubDate: 2019-09-02
      DOI: 10.3390/fi11090190
      Issue No: Vol. 11, No. 9 (2019)
  • Future Internet, Vol. 11, Pages 191: Social Network Services Management
           and Risk of Doocing. Comment on Kim, S.; Park, H.; Choi, M.J. “Negative
           Impact of Social Network Services Based on Stressor-Stress-Outcome: The
           Role of Experience of Privacy Violations. Future Internet 2019, 11, 137”

    • Authors: Stefania Fantinelli, Michela Cortini
      First page: 191
      Abstract: In light of the recent work by Kim and colleagues about Social Network Service (SNS), examining the individual and SNS characteristics as predictors of SNS fatigue, we hypothesize to enlarge their model to the job context. SNS is a relevant issue in occupational life as employers use it to have a deeper knowledge of their employees and as a tool of corporate communication. Employees can use SNS as a social platform and as a way to express discontent. In this latter case, the organization can implement a disciplinary procedure toward employees, known as doocing. The perception of privacy violation is strictly related to the fear and awareness of doocing, which in turn can predict SNS fatigue as well. So, it could be worthwhile to extend Kim and colleagues’ model to the workplace with particular attention to the doocing phenomenon.
      Citation: Future Internet
      PubDate: 2019-09-04
      DOI: 10.3390/fi11090191
      Issue No: Vol. 11, No. 9 (2019)
  • Future Internet, Vol. 11, Pages 192: A Framework for the Detection of
           Search and Rescue Patterns Using Shapelet Classification

    • Authors: Konstantinos Kapadais, Iraklis Varlamis, Christos Sardianos, Konstantinos Tserpes
      First page: 192
      Abstract: The problem of unmanned supervision of maritime areas has attracted the interest of researchers for the last few years, mainly thanks to the advances in vessel monitoring that the Automatic Identification System (AIS) has brought. Several frameworks and algorithms have been proposed for the management of vessel trajectory data, which focus on data compression, data clustering, classification and visualization, offering a wide variety of solutions from vessel monitoring to automatic detection of complex events. This work builds on our previous work in the topic of automatic detection of Search and Rescue (SAR) missions, by developing and evaluating a methodology for classifying the trajectories of vessels that possibly participate in such missions. The proposed solution takes advantage of a synthetic trajectory generator and a classifier that combines a genetic algorithm (GENDIS) for the extraction of informative shapelets from training data and a transformation to the shapelets’ feature space. Using the generator and several SAR patterns that are formally described in naval operations bibliography, it generates a synthetic dataset that is used to train the classifier. Evaluation on both synthetic and real data has very promising results and helped us to identify vessel SAR maneuvers without putting any effort into manual annotation.
      Citation: Future Internet
      PubDate: 2019-09-04
      DOI: 10.3390/fi11090192
      Issue No: Vol. 11, No. 9 (2019)
  • Future Internet, Vol. 11, Pages 193: Satellite Integration into 5G: Accent
           on First Over-The-Air Tests of an Edge Node Concept with Integrated
           Satellite Backhaul

    • Authors: Florian Völk, Konstantinos Liolis, Marius Corici, Joe Cahill, Robert Schwarz, Thomas Schlichter, Eric Troudt, Andreas Knopp
      First page: 193
      Abstract: The 5G vision embraces a broad range of applications including the connectivity in underserved and remote areas. In particular, for these applications, satellites are going to play a role in future 5G networks to provide capacity on trains, vessels, aircraft, and for base stations around the globe. In this paper, a 5G edge node concept, developed and evaluated with over-the-air tests using satellites in the geostationary orbit, is presented. The article covers a testbed demonstration study in Europe with a large-scale testbed including satellites and the latest standardization for the network architecture. The main goal of this testbed is to evaluate how satellite networks can be best integrated within the convergent 5G environment. The over-the-air tests for 5G satellite integration in this article are based on a 3GPP Release 15 core network architecture.
      Citation: Future Internet
      PubDate: 2019-09-05
      DOI: 10.3390/fi11090193
      Issue No: Vol. 11, No. 9 (2019)
  • Future Internet, Vol. 11, Pages 194: 25 Years of Bluetooth Technology

    • Authors: Sherali Zeadally, Farhan Siddiqui, Zubair Baig
      First page: 194
      Abstract: Bluetooth technology started off as a wireless, short-range cable replacement technology but it has undergone significant developments over the last two decades. Bluetooth radios are currently embedded in almost all computing devices including personal computers, smart phones, smart watches, and even micro-controllers. For many of us, Bluetooth is an essential technology that we use every day. We provide an insight into the history of Bluetooth and its significant design developments over the last 25 years. We also discuss related issues (including security) and Bluetooth as a driving technology for the Internet of Things (IoT). Finally, we also present recent research results obtained with Bluetooth technology in various application areas.
      Citation: Future Internet
      PubDate: 2019-09-09
      DOI: 10.3390/fi11090194
      Issue No: Vol. 11, No. 9 (2019)
  • Future Internet, Vol. 11, Pages 195: ERMOCTAVE: A Risk Management
           Framework for IT Systems Which Adopt Cloud Computing

    • Authors: Masky Mackita, Soo-Young Shin, Tae-Young Choe
      First page: 195
      Abstract: Many companies are adapting cloud computing technology because moving to the cloud has an array of benefits. During decision-making, having processed for adopting cloud computing, the importance of risk management is progressively recognized. However, traditional risk management methods cannot be applied directly to cloud computing when data are transmitted and processed by external providers. When they are directly applied, risk management processes can fail by ignoring the distributed nature of cloud computing and leaving numerous risks unidentified. In order to fix this backdrop, this paper introduces a new risk management method, Enterprise Risk Management for Operationally Critical Threat, Asset, and Vulnerability Evaluation (ERMOCTAVE), which combines Enterprise Risk Management and Operationally Critical Threat, Asset, and Vulnerability Evaluation for mitigating risks that can arise with cloud computing. ERMOCTAVE is composed of two risk management methods by combining each component with another processes for comprehensive perception of risks. In order to explain ERMOCTAVE in detail, a case study scenario is presented where an Internet seller migrates some modules to Microsoft Azure cloud. The functionality comparison with ENISA and Microsoft cloud risk assessment shows that ERMOCTAVE has additional features, such as key objectives and strategies, critical assets, and risk measurement criteria.
      Citation: Future Internet
      PubDate: 2019-09-10
      DOI: 10.3390/fi11090195
      Issue No: Vol. 11, No. 9 (2019)
  • Future Internet, Vol. 11, Pages 196: Evaluating the Degree of Uncertainty
           of Research Activities in Industry 4.0

    • Authors: Sirio Cividino, Gianluca Egidi, Ilaria Zambon, Andrea Colantoni
      First page: 196
      Abstract: Research and development (R&D) are always oriented towards new discoveries, based on original terms or hypotheses, and their concluding outcomes are often uncertain. The present work focused on the degree of uncertainty for R&D activities. In fact, uncertainty makes it difficult to quantify the time and resources needed to achieve a final outcome, create a work plan and budget, and finalize the resulting “innovative” products or services that could be transferred or exchanged in a specific market. The present work attempts to indicate the degree of uncertainty of the research activities developed by a set of firms. The method used aimed to quantify the five criteria defined by the Manual of Frascati. Through the creation of an uncertainty cloud, a cone of uncertainty was defined following an approach based on project management. The evaluation grid was characterized by the decomposition of the different variables divided into quartiles, which allowed for the detection of the evolution of the project and each of its component. The ancillary objective aim was to also observe the development degree of these industries towards a framework of Industry 4.0.
      Citation: Future Internet
      PubDate: 2019-09-11
      DOI: 10.3390/fi11090196
      Issue No: Vol. 11, No. 9 (2019)
  • Future Internet, Vol. 11, Pages 197: MU R-CNN: A Two-Dimensional Code
           Instance Segmentation Network Based on Deep Learning

    • Authors: Baoxi Yuan, Yang Li, Fan Jiang, Xiaojie Xu, Yingxia Guo, Jianhua Zhao, Deyue Zhang, Jianxin Guo, Xiaoli Shen
      First page: 197
      Abstract: In the context of Industry 4.0, the most popular way to identify and track objects is to add tags, and currently most companies still use cheap quick response (QR) tags, which can be positioned by computer vision (CV) technology. In CV, instance segmentation (IS) can detect the position of tags while also segmenting each instance. Currently, the mask region-based convolutional neural network (Mask R-CNN) method is used to realize IS, but the completeness of the instance mask cannot be guaranteed. Furthermore, due to the rich texture of QR tags, low-quality images can lower intersection-over-union (IoU) significantly, disabling it from accurately measuring the completeness of the instance mask. In order to optimize the IoU of the instance mask, a QR tag IS method named the mask UNet region-based convolutional neural network (MU R-CNN) is proposed. We utilize the UNet branch to reduce the impact of low image quality on IoU through texture segmentation. The UNet branch does not depend on the features of the Mask R-CNN branch so its training process can be carried out independently. The pre-trained optimal UNet model can ensure that the loss of MU R-CNN is accurate from the beginning of the end-to-end training. Experimental results show that the proposed MU R-CNN is applicable to both high- and low-quality images, and thus more suitable for Industry 4.0.
      Citation: Future Internet
      PubDate: 2019-09-13
      DOI: 10.3390/fi11090197
      Issue No: Vol. 11, No. 9 (2019)
  • Future Internet, Vol. 11, Pages 198: Dynamic Group Recommendation Based on
           the Attention Mechanism

    • Authors: Haiyan Xu, Yanhui Ding, Jing Sun, Kun Zhao, Yuanjian Chen
      First page: 198
      Abstract: Group recommendation has attracted significant research efforts for its importance in benefiting group members. The purpose of group recommendation is to provide recommendations to group users, such as recommending a movie to several friends. Group recommendation requires that the recommendation should be as satisfactory as possible to each member of the group. Due to the lack of weighting of users in different items, group decision-making cannot be made dynamically. Therefore, in this paper, a dynamic recommendation method based on the attention mechanism is proposed. Firstly, an improved density peak clustering ( DPC ) algorithm is used to discover the potential group; and then the attention mechanism is adopted to learn the influence weight of each user. The normalized discounted cumulative gain (NDCG) and hit ratio (HR) are adopted to evaluate the validity of the recommendation results. Experimental results on the CAMRa2011 dataset show that our method is effective.
      Citation: Future Internet
      PubDate: 2019-09-17
      DOI: 10.3390/fi11090198
      Issue No: Vol. 11, No. 9 (2019)
  • Future Internet, Vol. 11, Pages 199: Enhancing the 3GPP V2X Architecture
           with Information-Centric Networking

    • Authors: Marica Amadeo, Claudia Campolo, Antonella Molinaro, Jerome Harri, Christian Esteve Rothenberg, Alexey Vinel
      First page: 199
      Abstract: Vehicle-to-everything (V2X) communications allow a vehicle to interact with other vehicles and with communication parties in its vicinity (e.g., road-side units, pedestrian users, etc.) with the primary goal of making the driving and traveling experience safer, smarter and more comfortable. A wide set of V2X-tailored specifications have been identified by the Third Generation Partnership Project (3GPP) with focus on the design of architecture enhancements and a flexible air interface to ensure ultra-low latency, highly reliable and high-throughput connectivity as the ultimate aim. This paper discusses the potential of leveraging Information-Centric Networking (ICN) principles in the 3GPP architecture for V2X communications. We consider Named Data Networking (NDN) as reference ICN architecture and elaborate on the specific design aspects, required changes and enhancements in the 3GPP V2X architecture to enable NDN-based data exchange as an alternative/complementary solution to traditional IP networking, which barely matches the dynamics of vehicular environments. Results are provided to showcase the performance improvements of the NDN-based proposal in disseminating content requests over the cellular network against a traditional networking solution.
      Citation: Future Internet
      PubDate: 2019-09-18
      DOI: 10.3390/fi11090199
      Issue No: Vol. 11, No. 9 (2019)
  • Future Internet, Vol. 11, Pages 200: Incorporating Background Checks with
           Sentiment Analysis to Identify Violence Risky Chinese Microblogs

    • Authors: Yun-Fei Jia, Shan Li, Renbiao Wu
      First page: 200
      Abstract: Based on Web 2.0 technology, more and more people tend to express their attitude or opinions on the Internet. Radical ideas, rumors, terrorism, or violent contents are also propagated on the Internet, causing several incidents of social panic every year in China. In fact, most of this content comprises joking or emotional catharsis. To detect this with conventional techniques usually incurs a large false alarm rate. To address this problem, this paper introduces a technique that combines sentiment analysis with background checks. State-of-the-art sentiment analysis usually depends on training datasets in a specific topic area. Unfortunately, for some domains, such as violence risk speech detection, there is no definitive training data. In particular, topic-independent sentiment analysis of short Chinese text has been rarely reported in the literature. In this paper, the violence risk of the Chinese microblogs is calculated from multiple perspectives. First, a lexicon-based method is used to retrieve violence-related microblogs, and then a similarity-based method is used to extract sentiment words. Semantic rules and emoticons are employed to obtain the sentiment polarity and sentiment strength of short texts. Second, the activity risk is calculated based on the characteristics of part of speech (PoS) sequence and by semantic rules, and then a threshold is set to capture the key users. Finally, the risk is confirmed by historical speeches and the opinions of the friend-circle of the key users. The experimental results show that the proposed approach outperforms the support vector machine (SVM) method on a topic-independent corpus and can effectively reduce the false alarm rate.
      Citation: Future Internet
      PubDate: 2019-09-19
      DOI: 10.3390/fi11090200
      Issue No: Vol. 11, No. 9 (2019)
  • Future Internet, Vol. 11, Pages 201: Role-Mining Optimization with

    • Authors: Wei Sun, Shiwei Wei, Huaping Guo, Hongbing Liu
      First page: 201
      Abstract: Role-based access control (RBAC), which has been regarded as one of the most popular access-control mechanisms, is featured by the separation-of-duty constraints, mutually exclusive constraints, and the least-privileges principle. Role mining, a bottom-up role-engineering technology, is an effective method to migrate from a non-RBAC system to an RBAC system. However, conventional role-mining approaches not only do not consider the separation of duty constraints, but also cannot ensure the security of a constructed RBAC system when the corresponding mined results violate the separation of a duty constraint and/or the least-privileges principle. To solve these problems, this paper proposes a novel method called role-mining optimization with separation-of-duty constraints and security detections for authorizations (RMO_SODSDA), which mainly includes two aspects. First, we present a role-mining-optimization approach for satisfying the separation of duty constraints, and we constructed different variants of mutually exclusive constraints to correctly implement the given separation of duty constraints based on unconstrained role mining. Second, to ensure the security of the constructed system and evaluate authorization performance, we reduced the authorization-query problem to a maximal-satisfiability problem. The experiments validate the effectiveness and efficiency of the proposed method.
      Citation: Future Internet
      PubDate: 2019-09-19
      DOI: 10.3390/fi11090201
      Issue No: Vol. 11, No. 9 (2019)
  • Future Internet, Vol. 11, Pages 202: Ranking by Relevance and Citation
           Counts, a Comparative Study: Google Scholar, Microsoft Academic, WoS and

    • Authors: Cristòfol Rovira, Lluís Codina, Frederic Guerrero-Solé, Carlos Lopezosa
      First page: 202
      Abstract: Search engine optimization (SEO) constitutes the set of methods designed to increase the visibility of, and the number of visits to, a web page by means of its ranking on the search engine results pages. Recently, SEO has also been applied to academic databases and search engines, in a trend that is in constant growth. This new approach, known as academic SEO (ASEO), has generated a field of study with considerable future growth potential due to the impact of open science. The study reported here forms part of this new field of analysis. The ranking of results is a key aspect in any information system since it determines the way in which these results are presented to the user. The aim of this study is to analyze and compare the relevance ranking algorithms employed by various academic platforms to identify the importance of citations received in their algorithms. Specifically, we analyze two search engines and two bibliographic databases: Google Scholar and Microsoft Academic, on the one hand, and Web of Science and Scopus, on the other. A reverse engineering methodology is employed based on the statistical analysis of Spearman’s correlation coefficients. The results indicate that the ranking algorithms used by Google Scholar and Microsoft are the two that are most heavily influenced by citations received. Indeed, citation counts are clearly the main SEO factor in these academic search engines. An unexpected finding is that, at certain points in time, Web of Science (WoS) used citations received as a key ranking factor, despite the fact that WoS support documents claim this factor does not intervene.
      Citation: Future Internet
      PubDate: 2019-09-19
      DOI: 10.3390/fi11090202
      Issue No: Vol. 11, No. 9 (2019)
  • Future Internet, Vol. 11, Pages 203: Vehicular Delay-Tolerant Networks
           with Image Recognition-Based Adaptive Array Antenna for Winter Road
           Surveillance in Local Areas

    • Authors: Noriki Uchida, Goshi Sato, Yoshitaka Shibata
      First page: 203
      Abstract: The rapid growth of the ITS (intelligent transport system) development requires us to realize new kinds of applications, such as the winter road surveillance system. However, it is still necessary to consider the network difficulty areas for LTE (long-term evolution) or 3G transmissions when one visits sightseeing spots such as ski resorts or spas in mountain areas. Therefore, this paper proposes a winter road surveillance system in the local area based on vehicular delay-tolerant networks. The adaptive array antenna controlled by image recognition with the Kalman filter algorithm is proposed as well to the system in order to realize higher delivery rates. The implementations of the prototype system are presented in this paper as well, and the effectivity of the radio transmission in the prototype system is realized by vehicular image recognition methods and the asynchronous voltage controls for antenna elements for the rapid directional controls of the radio transmission. The experimental results showed that the radio directional controls by the prototype system for the target vehicle can proceed within one second, and that the simulation with the GIS (geographic information system) map pointed out the delivery rates of the proposed method—which are better than those of the epidemic DTN (delay-tolerant networking) routing by the nondirectional antenna. The experiments of the proposed methods indicate a higher efficiency of the data transmissions—even in the mountain area. Furthermore, future research subjects are discussed in this paper.
      Citation: Future Internet
      PubDate: 2019-09-19
      DOI: 10.3390/fi11090203
      Issue No: Vol. 11, No. 9 (2019)
  • Future Internet, Vol. 11, Pages 164: Energy Efficient Communications for
           Reliable IoT Multicast 5G/Satellite Services

    • Authors: Francesco Chiti, Romano Fantacci, Laura Pierucci
      First page: 164
      Abstract: Satellites can provide strong value-add and complementarity with the new cellular system of the fifth generation (5G) in cost-effective solutions for a massive number of users/devices/things. Due to the inherent broadcast nature of satellite communications, which assures access to remote areas and the support to a very large number of devices, satellite systems will gain a major role in the development of the Internet of Things (IoT) sector. In this vision, reliable multicast services via satellite can be provided to deliver the same content efficiently to multiple devices on the Earth, or for software updating to groups of cars in the Machine-to-Machine (M2M) context or for sending control messages to actuators/IoT embedded devices. The paper focuses on the Network coding (NC) techniques applied to a hybrid satellite/terrestrial network to support reliable multicast services. An energy optimization method is proposed based on joint adaptation of: (i) the repetition factor of data symbols on multiple subcarries of the transmitted orthogonal frequency division multiplexing (OFDM) signal; and (ii) the mean number of needed coded packets according to the requirements of each group and to the physical satellite links conditions.
      Citation: Future Internet
      PubDate: 2019-07-25
      DOI: 10.3390/fi11080164
      Issue No: Vol. 11, No. 8 (2019)
  • Future Internet, Vol. 11, Pages 165: Social Emotional Opinion Decision

    • Authors: Jin Sol Yang, Myung-Sook Ko, Kwang Sik Chung
      First page: 165
      Abstract: Nowadays, based on mobile devices and internet, social network services (SNS) are common trends to everyone. Social opinions as public opinions are very important to the government, company, and a person. Analysis and decision of social polarity of SNS about social happenings, political issues and government policies, or commercial products is very critical to the government, company, and a person. Newly coined words and emoticons on SNS are created every day. Specifically, emoticons are made and sold by a person or companies. Newly coined words are mostly made and used by various kinds of communities. The SNS big data mainly consist of normal text with newly coined words and emoticons so that newly coined words and emoticons analysis is very important to understand the social and public opinions. Social big data is informally made and unstructured, and on social network services, many kinds of newly coined words and various emoticons are made anonymously and unintentionally by people and companies. In the analysis of social data, newly coined words and emoticons limit the guarantee the accuracy of analysis. The newly coined words implicitly contain the social opinions and trends of people. The emotional states of people significantly are expressed by emoticons. Although the newly coined words and emoticons are an important part of the social opinion analysis, they are excluded from the emotional dictionary and social big data analysis. In this research, newly coined words and emoticons are extracted from the raw Twitter’s twit messages and analyzed and included in a pre-built dictionary with the polarity and weight of the newly coined words and emoticons. The polarity and weight are calculated for emotional classification. The proposed emotional classification algorithm calculates the weight of polarity (positive or negative) and results in total polarity weight of social opinion. If the total polarity weight of social opinion is more than the pre-fixed threshold value, the twit message is decided as positive. If it is less than the pre-fixed threshold value, the twit message is decided as negative and the other values mean neutral opinion. The accuracy of the social big data analysis result is improved by quantifying and analyzing emoticons and newly coined words.
      Citation: Future Internet
      PubDate: 2019-07-25
      DOI: 10.3390/fi11080165
      Issue No: Vol. 11, No. 8 (2019)
  • Future Internet, Vol. 11, Pages 166: Software Defined Wireless Mesh
           Network Flat Distribution Control Plane

    • Authors: Hisham Elzain, Yang Wu
      First page: 166
      Abstract: Wireless Mesh Networks (WMNs), have a potential offering relatively stable Internet broadband access. The rapid development and growth of WMNs attract ISPs to support users’ coverage anywhere anytime. To achieve this goal network architecture must be addressed carefully. Software Defined Networking (SDN) proposes new network architecture for wired and wireless networks. Software Defined Wireless Networking (SDWN) has a great potential to increase efficiency, ease the complexity of control and management, and accelerate technology innovation rate of wireless networking. An SDN controller is the core component of an SDN network. It needs to have updated reports of the network status change, as in network topology and quality of service (QoS) in order to effectively configure and manage the network it controls. In this paper, we propose Flat Distributed Software Defined Wireless Mesh Network architecture where the controller aggregates entire topology discovery and monitors QoS properties of extended WMN nodes using Link Layer Discovery Protocol (LLDP) protocol, which is not possible in multi-hop ordinary architectures. The proposed architecture has been implemented on top of POX controller and Advanced Message Queuing Protocol (AMQP) protocol. The experiments were conducted in a Mininet-wifi emulator, the results present the architecture control plane consistency and two application cases: topology discovery and QoS monitoring. The current results push us to study QoS-routing for video streaming over WMN.
      Citation: Future Internet
      PubDate: 2019-07-25
      DOI: 10.3390/fi11080166
      Issue No: Vol. 11, No. 8 (2019)
  • Future Internet, Vol. 11, Pages 167: A Hybrid Adaptive Transaction
           Injection Protocol and Its Optimization for Verification-Based
           Decentralized System

    • Authors: Saumendra Sengupta, Chen-Fu Chiang, Bruno Andriamanalimanana, Jorge Novillo, Ali Tekeoglu
      First page: 167
      Abstract: Latency is a critical issue that impacts the performance of decentralized systems. Recently we designed various protocols to regulate the injection rate of unverified transactions into the system to improve system performance. Each of the protocols is designed to address issues related to some particular network traffic syndrome. In this work, we first provide the review of our prior protocols. We then provide a hybrid scheme that combines our transaction injection protocols and provides an optimal linear combination of the protocols based on the syndromes in the network. The goal is to speed up the verification process of systems that rely on only one single basic protocol. The underlying basic protocols are Periodic Injection of Transaction via Evaluation Corridor (PITEC), Probabilistic Injection of Transactions (PIT), and Adaptive Semi-synchronous Transaction Injection (ASTI).
      Citation: Future Internet
      PubDate: 2019-07-27
      DOI: 10.3390/fi11080167
      Issue No: Vol. 11, No. 8 (2019)
  • Future Internet, Vol. 11, Pages 168: Latency-Based Dynamic Controller
           Assignment in Hybrid SDNs: Considering the Impact of Legacy Routers

    • Authors: Jie Yuan, Erxia Li, Chaoqun Kang, Fangyuan Chang, Tingting Yuan, Xiaoyong Li
      First page: 168
      Abstract: Software-defined networking (SDN) is a modern network architecture, which separates the network control plane from the data plane. Considering the gradual migration from traditional networks to SDNs, the hybrid SDN, which consists of SDN-enabled devices and legacy devices, is an intermediate state. For wide-area hybrid SDNs, to guarantee the control performance, such as low latency, multi SDN controllers are usually needed to be deployed at different places. How to assign them to switches and partition the network into several control domains is a critical problem. For this problem, the control latency and the packet loss rate of control messages are important metrics, which have been considered in a lot of previous works. However, hybrid SDNs have their unique characters, which can affect the assignment scheme and have been ignored by previous studies. For example, control messages pass through Legacy Forwarding Devices (LFDs) in hybrid SDNs and cause more latency and packet loss rate for queuing compared with SDN-enabled Forwarding Devices (SFDs). In this paper, we propose a dynamic controller assignment scheme in hybrid SDNs, which is called the Legacy Based Assignment (LBA). This scheme can dynamically delegate each controller with a subset of SFDs in the hybrid SDNs, whose objective is to minimize average SFD-to-control latency. We performed some experiments compared with other schemes, which show that our scheme has a better performance in terms of the latency and the packet loss rate.
      Citation: Future Internet
      PubDate: 2019-07-28
      DOI: 10.3390/fi11080168
      Issue No: Vol. 11, No. 8 (2019)
  • Future Internet, Vol. 11, Pages 169: An Image Feature-Based Method for
           Parking Lot Occupancy

    • Authors: Paula Tătulea, Florina Călin, Remus Brad, Lucian Brâncovean, Mircea Greavu
      First page: 169
      Abstract: The main scope of the presented research was the development of an innovative product for the management of city parking lots. Our application will ensure the implementation of the Smart City concept by using computer vision and communication platforms, which enable the development of new integrated digital services. The use of video cameras could simplify and lower the costs of parking lot controls. In the aim of parking space detection, an aggregated decision was proposed, employing various metrics, computed over a sliding window interval provided by the camera. The history created over 20 images provides an adaptive method for background and accurate detection. The system has shown high robustness in two benchmarks, achieving a recognition rate higher than 93%.
      Citation: Future Internet
      PubDate: 2019-08-01
      DOI: 10.3390/fi11080169
      Issue No: Vol. 11, No. 8 (2019)
  • Future Internet, Vol. 11, Pages 170: Artificial Intelligence
           Implementations on the Blockchain. Use Cases and Future Applications

    • Authors: Konstantinos Sgantzos, Ian Grigg
      First page: 170
      Abstract: An exemplary paradigm of how an AI can be a disruptive technological paragon via the utilization of blockchain comes straight from the world of deep learning. Data scientists have long struggled to maintain the quality of a dataset for machine learning by an AI entity. Datasets can be very expensive to purchase, as, depending on both the proper selection of the elements and the homogeneity of the data contained within, constructing and maintaining the integrity of a dataset is difficult. Blockchain as a highly secure storage medium presents a technological quantum leap in maintaining data integrity. Furthermore, blockchain’s immutability constructs a fruitful environment for creating high quality, permanent and growing datasets for deep learning. The combination of AI and blockchain could impact fields like Internet of things (IoT), identity, financial markets, civil governance, smart cities, small communities, supply chains, personalized medicine and other fields, and thereby deliver benefits to many people.
      Citation: Future Internet
      PubDate: 2019-08-02
      DOI: 10.3390/fi11080170
      Issue No: Vol. 11, No. 8 (2019)
  • Future Internet, Vol. 11, Pages 171: Modeling of Cumulative QoE in
           On-Demand Video Services: Role of Memory Effect and Degree of Interest

    • Authors: Tho Nguyen Duc, Chanh Minh Tran, Phan Xuan Tan, Eiji Kamioka
      First page: 171
      Abstract: The growing demand on video streaming services increasingly motivates the development of a reliable and accurate models for the assessment of Quality of Experience (QoE). In this duty, human-related factors which have significant influence on QoE play a crucial role. However, the complexity caused by multiple effects of those factors on human perception has introduced challenges on contemporary studies. In this paper, we inspect the impact of the human-related factors, namely perceptual factors, memory effect, and the degree of interest. Based on our investigation, a novel QoE model is proposed that effectively incorporates those factors to reflect the user’s cumulative perception. Evaluation results indicate that our proposed model performed excellently in predicting cumulative QoE at any moment within a streaming session.
      Citation: Future Internet
      PubDate: 2019-08-04
      DOI: 10.3390/fi11080171
      Issue No: Vol. 11, No. 8 (2019)
  • Future Internet, Vol. 11, Pages 172: Scheduling for Multi-User Multi-Input
           Multi-Output Wireless Networks with Priorities and Deadlines

    • Authors: Li-on Raviv, Amir Leshem
      First page: 172
      Abstract: The spectral efficiency of wireless networks can be significantly improved by exploiting spatial multiplexing techniques known as multi-user MIMO. These techniques enable the allocation of multiple users to the same time-frequency block, thus reducing the interference between users. There is ample evidence that user groupings can have a significant impact on the performance of spatial multiplexing. The situation is even more complex when the data packets have priority and deadlines for delivery. Hence, combining packet queue management and beamforming would considerably enhance the overall system performance. In this paper, we propose a combination of beamforming and scheduling to improve the overall performance of multi-user MIMO systems in realistic conditions where data packets have both priority and deadlines beyond which they become obsolete. This method dubbed Reward Per Second (RPS), combines advanced matrix factorization at the physical layer with recently-developed queue management techniques. We demonstrate the merits of the this technique compared to other state-of-the-art scheduling methods through simulations.
      Citation: Future Internet
      PubDate: 2019-08-05
      DOI: 10.3390/fi11080172
      Issue No: Vol. 11, No. 8 (2019)
  • Future Internet, Vol. 11, Pages 173: Mars to Earth Data Downloading: A
           Directory Synchronization Approach

    • Authors: Marco Bertolazzi, Carlo Caini
      First page: 173
      Abstract: This paper aims to present a possible alternative to direct file transfer in “challenged networks”, by using DTNbox, a recent application for peer-to-peer directory synchronization between DTN nodes. This application uses the Bundle Protocol (BP) to tackle long delays and link intermittency typical of challenged networks. The directory synchronization approach proposed in the paper consists of delegating the transmission of bulk data files to DTNbox, instead of modifying source applications to interface with the API of a specific BP implementation, or making use of custom scripts for file transfers. The validity of the proposed approach is investigated in the paper by considering a Mars to Earth interplanetary environment. Experiments are carried out by means of Virtual Machines running ION, the NASA-JPL implementation of DTN protocols. The results show that the directory synchronization approach is a valid alternative to direct transfer in interplanetary scenarios such as that considered in the paper.
      Citation: Future Internet
      PubDate: 2019-08-08
      DOI: 10.3390/fi11080173
      Issue No: Vol. 11, No. 8 (2019)
  • Future Internet, Vol. 11, Pages 174: A Systematic Analysis of Real-World
           Energy Blockchain Initiatives

    • Authors: Peter O’Donovan, Dominic T. J. O’Sullivan
      First page: 174
      Abstract: The application of blockchain technology to the energy sector promises to derive new operating models focused on local generation and sustainable practices, which are driven by peer-to-peer collaboration and community engagement. However, real-world energy blockchains differ from typical blockchain networks insofar as they must interoperate with grid infrastructure, adhere to energy regulations, and embody engineering principles. Naturally, these additional dimensions make real-world energy blockchains highly dependent on the participation of grid operators, engineers, and energy providers. Although much theoretical and proof-of-concept research has been published on energy blockchains, this research aims to establish a lens on real-world projects and implementations that may inform the alignment of academic and industry research agendas. This research classifies 131 real-world energy blockchain initiatives to develop an understanding of how blockchains are being applied to the energy domain, what type of failure rates can be observed from recently reported initiatives, and what level of technical and theoretical details are reported for real-world deployments. The results presented from the systematic analysis highlight that real-world energy blockchains are (a) growing exponentially year-on-year, (b) producing relatively low failure/drop-off rates (~7% since 2015), and (c) demonstrating information sharing protocols that produce content with insufficient technical and theoretical depth.
      Citation: Future Internet
      PubDate: 2019-08-10
      DOI: 10.3390/fi11080174
      Issue No: Vol. 11, No. 8 (2019)
  • Future Internet, Vol. 11, Pages 175: Quality of Experience (QoE)-Aware
           Fast Coding Unit Size Selection for HEVC Intra-Prediction

    • Authors: Buddhiprabha Erabadda, Thanuja Mallikarachchi, Chaminda Hewage, Anil Fernando
      First page: 175
      Abstract: The exorbitant increase in the computational complexity of modern video coding standards, such as High Efficiency Video Coding (HEVC), is a compelling challenge for resource-constrained consumer electronic devices. For instance, the brute force evaluation of all possible combinations of available coding modes and quadtree-based coding structure in HEVC to determine the optimum set of coding parameters for a given content demand a substantial amount of computational and energy resources. Thus, the resource requirements for real time operation of HEVC has become a contributing factor towards the Quality of Experience (QoE) of the end users of emerging multimedia and future internet applications. In this context, this paper proposes a content-adaptive Coding Unit (CU) size selection algorithm for HEVC intra-prediction. The proposed algorithm builds content-specific weighted Support Vector Machine (SVM) models in real time during the encoding process, to provide an early estimate of CU size for a given content, avoiding the brute force evaluation of all possible coding mode combinations in HEVC. The experimental results demonstrate an average encoding time reduction of 52.38%, with an average Bjøntegaard Delta Bit Rate (BDBR) increase of 1.19% compared to the HM16.1 reference encoder. Furthermore, the perceptual visual quality assessments conducted through Video Quality Metric (VQM) show minimal visual quality impact on the reconstructed videos of the proposed algorithm compared to state-of-the-art approaches.
      Citation: Future Internet
      PubDate: 2019-08-11
      DOI: 10.3390/fi11080175
      Issue No: Vol. 11, No. 8 (2019)
  • Future Internet, Vol. 11, Pages 176: Research on Factors Affecting
           Solvers’ Participation Time in Online Crowdsourcing Contests

    • Authors: Keng Yang
      First page: 176
      Abstract: A crowdsourcing contest is one of the most popular modes of crowdsourcing and is also an important tool for an enterprise to implement open innovation. The solvers’ active participation is one of the major reasons for the success of crowdsourcing contests. Research on solvers’ participation behavior is helpful in understanding the sustainability and incentives of solvers’ participation in the online crowdsourcing platform. So, how to attract more solvers to participate and put in more effort is the focus of researchers. In this regard, previous studies mainly used the submission quantity to measure solvers’ participation behavior and lacked an effective measure on the degree of participation effort expended by a solver. For the first time, we use solvers’ participation time as a dependent variable to measure their effort in a crowdsourcing contest. Thus, we incorporate participation time into the solver’s participation research. With the data from, we analyze how participation time is affected four key factors including task design, task description, task process, and environment, respectively. We found that, first, for task design, higher task rewards will attract solvers to invest more time in the participation process and the relationship between participation time and task duration is inverted U-shaped. Second, for task description, the length of the task description has a negative impact on participation time and the task description attachment will positively influence the participation time. Third, for the task process, communication and supplementary explanations in a crowdsourcing process positively affect participation time. Fourth, for environmental factors, the task density of the crowdsourcing platform and the market price of all crowdsourcing contests have respectively negative and positive effects on participation time.
      Citation: Future Internet
      PubDate: 2019-08-12
      DOI: 10.3390/fi11080176
      Issue No: Vol. 11, No. 8 (2019)
  • Future Internet, Vol. 11, Pages 177: RLXSS: Optimizing XSS Detection Model
           to Defend Against Adversarial Attacks Based on Reinforcement Learning

    • Authors: Yong Fang, Cheng Huang, Yijia Xu, Yang Li
      First page: 177
      Abstract: With the development of artificial intelligence, machine learning algorithms and deep learning algorithms are widely applied to attack detection models. Adversarial attacks against artificial intelligence models become inevitable problems when there is a lack of research on the cross-site scripting (XSS) attack detection model for defense against attacks. It is extremely important to design a method that can effectively improve the detection model against attack. In this paper, we present a method based on reinforcement learning (called RLXSS), which aims to optimize the XSS detection model to defend against adversarial attacks. First, the adversarial samples of the detection model are mined by the adversarial attack model based on reinforcement learning. Secondly, the detection model and the adversarial model are alternately trained. After each round, the newly-excavated adversarial samples are marked as a malicious sample and are used to retrain the detection model. Experimental results show that the proposed RLXSS model can successfully mine adversarial samples that escape black-box and white-box detection and retain aggressive features. What is more, by alternately training the detection model and the confrontation attack model, the escape rate of the detection model is continuously reduced, which indicates that the model can improve the ability of the detection model to defend against attacks.
      Citation: Future Internet
      PubDate: 2019-08-14
      DOI: 10.3390/fi11080177
      Issue No: Vol. 11, No. 8 (2019)
  • Future Internet, Vol. 11, Pages 178: Artificial Intelligence Imagery
           Analysis Fostering Big Data Analytics

    • Authors: Stefan Cremer, Claudia Loebbecke
      First page: 178
      Abstract: In an era of accelerating digitization and advanced big data analytics, harnessing quality data and insights will enable innovative research methods and management approaches. Among others, Artificial Intelligence Imagery Analysis has recently emerged as a new method for analyzing the content of large amounts of pictorial data. In this paper, we provide background information and outline the application of Artificial Intelligence Imagery Analysis for analyzing the content of large amounts of pictorial data. We suggest that Artificial Intelligence Imagery Analysis constitutes a profound improvement over previous methods that have mostly relied on manual work by humans. In this paper, we discuss the applications of Artificial Intelligence Imagery Analysis for research and practice and provide an example of its use for research. In the case study, we employed Artificial Intelligence Imagery Analysis for decomposing and assessing thumbnail images in the context of marketing and media research and show how properly assessed and designed thumbnail images promote the consumption of online videos. We conclude the paper with a discussion on the potential of Artificial Intelligence Imagery Analysis for research and practice across disciplines.
      Citation: Future Internet
      PubDate: 2019-08-15
      DOI: 10.3390/fi11080178
      Issue No: Vol. 11, No. 8 (2019)
  • Future Internet, Vol. 11, Pages 179: Impact of Modern Virtualization
           Methods on Timing Precision and Performance of High-Speed Applications

    • Authors: Veronika Kirova, Kirill Karpov, Eduard Siemens, Irina Zander, Oksana Vasylenko, Dmitry Kachan, Sergii Maksymov
      First page: 179
      Abstract: The presented work is a result of extended research and analysis on timing methods precision, their efficiency in different virtual environments and the impact of timing precision on the performance of high-speed networks applications. We investigated how timer hardware is shared among heavily CPU- and I/O-bound tasks on a virtualized OS as well as on bare OS. By replacing the invoked timing methods within a well-known application for estimation of available path bandwidth, we provide the analysis of their impact on estimation accuracy. We show that timer overhead and precision are crucial for high-performance network applications, and low-precision timing methods usage, e.g., the delays and overheads issued by virtualization result in the degradation of the virtual environment. Furthermore, in this paper, we provide confirmation that, by using the methods we intentionally developed for both precise timing operations and AvB estimation, it is possible to overcome the inefficiency of standard time-related operations and overhead that comes with the virtualization. The impacts of negative virtualization factors were investigated in five different environments to define the most optimal virtual environment for high-speed network applications.
      Citation: Future Internet
      PubDate: 2019-08-16
      DOI: 10.3390/fi11080179
      Issue No: Vol. 11, No. 8 (2019)
  • Future Internet, Vol. 11, Pages 180: Combined Self-Attention Mechanism for
           Chinese Named Entity Recognition in Military

    • Authors: Fei Liao, Liangli Ma, Jingjing Pei, Linshan Tan
      First page: 180
      Abstract: Military named entity recognition (MNER) is one of the key technologies in military information extraction. Traditional methods for the MNER task rely on cumbersome feature engineering and specialized domain knowledge. In order to solve this problem, we propose a method employing a bidirectional long short-term memory (BiLSTM) neural network with a self-attention mechanism to identify the military entities automatically. We obtain distributed vector representations of the military corpus by unsupervised learning and the BiLSTM model combined with the self-attention mechanism is adopted to capture contextual information fully carried by the character vector sequence. The experimental results show that the self-attention mechanism can improve effectively the performance of MNER task. The F-score of the military documents and network military texts identification was 90.15% and 89.34%, respectively, which was better than other models.
      Citation: Future Internet
      PubDate: 2019-08-18
      DOI: 10.3390/fi11080180
      Issue No: Vol. 11, No. 8 (2019)
  • Future Internet, Vol. 11, Pages 181: A Novel Task Caching and Migration
           Strategy in Multi-Access Edge Computing Based on the Genetic Algorithm

    • Authors: Lujie Tang, Bing Tang, Linyao Kang, Li Zhang
      First page: 181
      Abstract: Multi-access edge computing (MEC) brings high-bandwidth and low-latency access to applications distributed at the edge of the network. Data transmission and exchange become faster, and the overhead of the task migration between mobile devices and edge cloud becomes smaller. In this paper, we adopt the fine-grained task migration model. At the same time, in order to further reduce the delay and energy consumption of task execution, the concept of the task cache is proposed, which involves caching the completed tasks and related data on the edge cloud. Then, we consider the limitations of the edge cloud cache capacity to study the task caching strategy and fine-grained task migration strategy on the edge cloud using the genetic algorithm (GA). Thus, we obtained the optimal mobile device task migration strategy, satisfying minimum energy consumption and the optimal cache on the edge cloud. The simulation results showed that the task caching strategy based on fine-grained migration can greatly reduce the energy consumption of mobile devices in the MEC environment.
      Citation: Future Internet
      PubDate: 2019-08-20
      DOI: 10.3390/fi11080181
      Issue No: Vol. 11, No. 8 (2019)
  • Future Internet, Vol. 11, Pages 146: Marine Internet for Internetworking
           in Oceans: A Tutorial

    • Authors: Shengming Jiang
      First page: 146
      Abstract: Ever-increasing human activities in oceans require handy, reliable and cost-effective high-speed network access similar to terrestrial Internet services to be available on and under water. However, terrestrial Internet cannot be extended to oceans seamlessly due to huge differences between terrestrial and oceanic environments, while satellite services are still very expensive especially for ordinary users with communication quality susceptible to weather conditions, and cannot cover underwater networks either. Therefore, marine Internet, proposed about six years ago, is the earliest scheme that tries to systematically address the internetworking issue in oceans and still in its infancy stage. This tutorial aims to introduce the principle, architecture and applications of marine Internet, along with discussion on oceanic environments for communication, currently available and under developing communication systems in oceans, as well as challenging issues necessary for further studies to foster the development of marine Internet.
      Citation: Future Internet
      PubDate: 2019-07-05
      DOI: 10.3390/fi11070146
      Issue No: Vol. 11, No. 7 (2019)
  • Future Internet, Vol. 11, Pages 147: Web Browser Network Based on a BA
           Model for a Web-Based Virtual World

    • Authors: Masaki Kohana, Shinji Sakamoto, Shusuke Okamoto
      First page: 147
      Abstract: Real-time web applications such as a virtual world require considerable computing resources. However, as the number of servers increases, so does the maintenance and financial cost. To share tasks among web browsers, the browsers must share data. Therefore, a network must be constructed among the web browsers. In this paper, we propose the construction of a web browser network based on the Barabasi–Albert model (BA model). We focus on a web-based multiplayer online game that requires higher frequent communication and significant computing resources. We attempt to optimize computing resource utilization for web browsers. We improve upon the method in our previous study, which constructed a network for a web-based virtual world, using only location information. When a new user logged into a world, the web browser connected to two other browsers whose users had a location close to that of the user. The experimental results of that method showed 50% data coverage, which was insufficient to display the game screen because the web browser displays the characters on the virtual world. In this study, we attempt to use the BA model to construct more efficient networks than those in the previous study to increase data coverage. Our new method uses the number of connections of the web browser and location information to calculate the probability of web browser selection. The experimental results show that the data coverage exceeds 90%, indicating significant improvement over the previous method.
      Citation: Future Internet
      PubDate: 2019-07-05
      DOI: 10.3390/fi11070147
      Issue No: Vol. 11, No. 7 (2019)
  • Future Internet, Vol. 11, Pages 148: The Effects of the Floating Action
           Button on Quality of Experience

    • Authors: Jesenka Pibernik, Jurica Dolic, Hrvoje Abraham Milicevic, Bojan Kanizaj
      First page: 148
      Abstract: Google’s Material Design, created in 2014, led to the extended application of floating action buttons (FAB) in user interfaces of web pages and mobile applications. FAB’s roll is to trigger an activity either on the present screen, or it can play out an activity that makes another screen. A few specialists in user experience (UX) and user interface (UI) design are sceptical regarding the usability of FAB in the interfaces of both web pages and mobile applications. They claim that the use of FAB easily distracts users and that it interferes with using other important functions of the applications, and it is unusable in applications designed for iOS systems. The aim of this paper is to investigate by an experiment the quality of experience (QoE) of a static and animated FAB and compare it to the toolbar alternative. The experimental results of different testing methods rejected the hypothesis that the usage and animation of this UI element has a positive influence on the application usability. However, its static and animated utilization enhanced the ratings of hedonic and aesthetic features of the user experience, justifying the usage of this type of button.
      Citation: Future Internet
      PubDate: 2019-07-06
      DOI: 10.3390/fi11070148
      Issue No: Vol. 11, No. 7 (2019)
  • Future Internet, Vol. 11, Pages 149: An Image Authentication Scheme Using
           Merkle Tree Mechanisms

    • Authors: Yi-Cheng Chen, Yueh-Peng Chou, Yung-Chen Chou
      First page: 149
      Abstract: Research on digital image processing has become quite popular and rapid in recent years, and scholars have proposed various image verification mechanisms. Similarly , blockchain technology has also become very popular in recent years. This paper proposes a new image verification mechanism based on the Merkle tree technique in the blockchain. The Merkle tree root in the blockchain mechanism provides a reliable environment for storage of image features. In image verification, the verification of each image can be performed by the Merkle tree mechanism to obtain the hash value of the Merkle tree node on the path. In addition, the method combines the Inter-Planetary File System (IPFS) to improve the availability of images. The main purpose of this paper is to achieve the goal of image integrity verification. The proposed method can not only verify the integrity of the image but also restore the tampered area in the case of image tampering. Since the proposed method employs the blockchain mechanism, the image verification mechanism does not need third party resources . The verification method is performed by each node in the blockchain network. The experimental results demonstrate that the proposed method successfully achieved the goal of image authentication and tampered area restoration.
      Citation: Future Internet
      PubDate: 2019-07-06
      DOI: 10.3390/fi11070149
      Issue No: Vol. 11, No. 7 (2019)
  • Future Internet, Vol. 11, Pages 150: Town-Watching Workshop Using Disaster
           Information Tweeting and Mapping System

    • Authors: Keisuke Utsu, Shun Ueta, Sachi Tajima, Yoshitaka Kajita, Yuji Murakami, Osamu Uchida
      First page: 150
      Abstract: Self- and mutual-help by citizens are important as well as social-help from the local governments, for disaster prevention and mitigation. Then, town watching and disaster prevention map-making workshops are held to review the town and promote self- and mutual-help by citizens. On the other hand, the use of social media for information sharing during and after disasters has been gaining attention. To facilitate information sharing in disasters, we developed a web system, Disaster Information Tweeting and Mapping System (DITS/DIMS). From the above background, we organized a town-watching workshop using DITS/DIMS in October 2018 in Minami Ward, Sapporo City, Hokkaido, Japan; affected area of the Hokkaido Eastern Iburi Earthquake in September 2018. In this paper, we explain the workshop procedure, outcome, questionnaire survey results, and post-meeting. The questionnaire survey result shows that the workshop educated the participants about posting useful information on social media during a disaster. In addition, at the post-meeting, the participants recognized that they had reviewed the town only from the perspective of “daily life” convenience before the earthquake, and they had not evaluated the “emergency viewpoint.” Therefore, the workshop was a meaningful opportunity for the participants to review the town in terms of disaster prevention and mitigation.
      Citation: Future Internet
      PubDate: 2019-07-07
      DOI: 10.3390/fi11070150
      Issue No: Vol. 11, No. 7 (2019)
  • Future Internet, Vol. 11, Pages 151: Structuring Reference Architectures
           for the Industrial Internet of Things

    • Authors: Sebastian R. Bader, Maria Maleshkova, Steffen Lohmann
      First page: 151
      Abstract: The ongoing digital transformation has the potential to revolutionize nearly all industrial manufacturing processes. However, its concrete requirements and implications are still not sufficiently investigated. In order to establish a common understanding, a multitude of initiatives have published guidelines, reference frameworks and specifications, all intending to promote their particular interpretation of the Industrial Internet of Things (IIoT). As a result of the inconsistent use of terminology, heterogeneous structures and proposed processes, an opaque landscape has been created. The consequence is that both new users and experienced experts can hardly manage to get an overview of the amount of information and publications, and make decisions on what is best to use and to adopt. This work contributes to the state of the art by providing a structured analysis of existing reference frameworks, their classifications and the concerns they target. We supply alignments of shared concepts, identify gaps and give a structured mapping of regarded concerns at each part of the respective reference architectures. Furthermore, the linking of relevant industry standards and technologies to the architectures allows a more effective search for specifications and guidelines and supports the direct technology adoption.
      Citation: Future Internet
      PubDate: 2019-07-08
      DOI: 10.3390/fi11070151
      Issue No: Vol. 11, No. 7 (2019)
  • Future Internet, Vol. 11, Pages 152: A Next-Generation Core Network
           Architecture for Mobile Networks

    • Authors: Andrea G. Forte, Wei Wang, Luca Veltri, Gianluigi Ferrari
      First page: 152
      Abstract: Over the years, the cellular mobile network has evolved from a wireless plain telephone system to a very complex system providing telephone service, Internet connectivity and many interworking capabilities with other networks. Its air interface performance has increased drastically over time, leading to high throughput and low latency. Changes to the core network, however, have been slow and incremental, with increased complexity worsened by the necessity of backwards-compatibility with older-generation systems such as the Global System for Mobile communication (GSM). In this paper, a new virtualized Peer-to-Peer (P2P) core network architecture is presented. The key idea of our approach is that each user is assigned a private virtualized copy of the whole core network. This enables a higher degree of security and novel services that are not possible in today’s architecture. We describe the new architecture, focusing on its main elements, IP addressing, message flows, mobility management, and scalability. Furthermore, we will show some significant advantages this new architecture introduces. Finally, we investigate the performance of our architecture by analyzing voice-call traffic available in a database of a large U.S. cellular network provider.
      Citation: Future Internet
      PubDate: 2019-07-09
      DOI: 10.3390/fi11070152
      Issue No: Vol. 11, No. 7 (2019)
  • Future Internet, Vol. 11, Pages 153: Architecting Software for the
           Internet of Thing Based Systems

    • Authors: Abdulrahman Alreshidi, Aakash Ahmad
      First page: 153
      Abstract: Context—Internet of Thing (IoT) based systems support any-time/place computations by interconnecting humans, systems, services, devices, and things that enabling autonomous systems to shape-up digitized societies. Software architecture, as the blue-print of software-intensive systems, abstracts the complexities of modeling, design, development, and evolution phases of a software to engineer complex IoT driven systems effectively and efficiently. Objectives and Method—Research and development efforts are required to exploit architectural principle and practices to design and develop IoT systems to go beyond the state-of-the-art for IoTs. The objectives of this research are to empirically investigate and systematically classify the state-of-the-art on architecting IoT based software. We have used the Evidence Based Software Engineering (EBSE) method to conduct a mapping study of the existing IoT solutions by investigating 88 qualitatively selected studies. Results and Implications—The results of the mapping study highlight various research themes that exploit software architecture models to develop IoT systems. The identified research themes include, but are not limited to, cloud-based software ecosystems, software defined networking, autonomous, and adaptive software and agent-based systems that IoTs drive. The mapping study suggests that futuristic research on architecting IoT software is focused on architectural languages and patterns that support reusability, automation, and human decision support to develop and dynamically adapt IoT software. The mapping study represents a concentrated knowledge regarding architectural principle and practices to facilitate knowledge transfer—benefiting researchers and practitioners—on the role of software architecture for IoT systems.
      Citation: Future Internet
      PubDate: 2019-07-10
      DOI: 10.3390/fi11070153
      Issue No: Vol. 11, No. 7 (2019)
  • Future Internet, Vol. 11, Pages 154: Signatures of the Crypto-Currency
           Market Decoupling from the Forex

    • Authors: Stanisław Drożdż, Ludovico Minati, Paweł Oświȩcimka, Marek Stanuszek, Marcin Wa̧torek
      First page: 154
      Abstract: Based on the high-frequency recordings from Kraken, a cryptocurrency exchange and professional trading platform that aims to bring Bitcoin and other cryptocurrencies into the mainstream, the multiscale cross-correlations involving the Bitcoin (BTC), Ethereum (ETH), Euro (EUR) and US dollar (USD) are studied over the period between 1 July 2016 and 31 December 2018. It is shown that the multiscaling characteristics of the exchange rate fluctuations related to the cryptocurrency market approach those of the Forex. This, in particular, applies to the BTC/ETH exchange rate, whose Hurst exponent by the end of 2018 started approaching the value of 0.5, which is characteristic of the mature world markets. Furthermore, the BTC/ETH direct exchange rate has already developed multifractality, which manifests itself via broad singularity spectra. A particularly significant result is that the measures applied for detecting cross-correlations between the dynamics of the BTC/ETH and EUR/USD exchange rates do not show any noticeable relationships. This could be taken as an indication that the cryptocurrency market has begun decoupling itself from the Forex.
      Citation: Future Internet
      PubDate: 2019-07-10
      DOI: 10.3390/fi11070154
      Issue No: Vol. 11, No. 7 (2019)
  • Future Internet, Vol. 11, Pages 155: Stacking-Based Ensemble Learning of
           Self-Media Data for Marketing Intention Detection

    • Authors: Yufeng Wang, Shuangrong Liu, Songqian Li, Jidong Duan, Zhihao Hou, Jia Yu, Kun Ma
      First page: 155
      Abstract: Social network services for self-media, such as Weibo, Blog, and WeChat Public, constitute a powerful medium that allows users to publish posts every day. Due to insufficient information transparency, malicious marketing of the Internet from self-media posts imposes potential harm on society. Therefore, it is necessary to identify news with marketing intentions for life. We follow the idea of text classification to identify marketing intentions. Although there are some current methods to address intention detection, the challenge is how the feature extraction of text reflects semantic information and how to improve the time complexity and space complexity of the recognition model. To this end, this paper proposes a machine learning method to identify marketing intentions from large-scale We-Media data. First, the proposed Latent Semantic Analysis (LSI)-Word2vec model can reflect the semantic features. Second, the decision tree model is simplified by decision tree pruning to save computing resources and reduce the time complexity. Finally, this paper examines the effects of classifier associations and uses the optimal configuration to help people efficiently identify marketing intention. Finally, the detailed experimental evaluation on several metrics shows that our approaches are effective and efficient. The F1 value can be increased by about 5%, and the running time is increased by 20%, which prove that the newly-proposed method can effectively improve the accuracy of marketing news recognition.
      Citation: Future Internet
      PubDate: 2019-07-10
      DOI: 10.3390/fi11070155
      Issue No: Vol. 11, No. 7 (2019)
  • Future Internet, Vol. 11, Pages 156: A Game Theoretic Interference
           Management Scheme in Full Duplex Cellular Systems under Infeasible QoS

    • Authors: Ali Y. Al-Zahrani
      First page: 156
      Abstract: Several emerging mobile applications and services (e.g., autonomous cars) require higher wireless throughput than ever before. This demand stresses the need for investigating novel methods that have the potential to dramatically increase the spectral efficiency (SE) of wireless systems. An evolving approach is the Single-channel full duplex (SCFD) communication where each node may simultaneously receive and transmit over the same frequency channel, and, hence, this could potentially double the current SE figures. In an earlier research work, we derived a model of the signal to interference plus noise ratio (SINR) in an SCFD-based cellular system with imperfect self interference cancellation, and investigated interference management under feasible QoS requirements. In this paper, game theoretic results are exploited to investigate the intercell interference management in SCFD-based cellular networks under infeasible QoS requirements. The investigation starts with a game formulation that captures two different cases. Then, the existence and uniqueness of the Nash equilibrium point are established. After that, a computationally efficient distributed algorithm, which realizes best effort and fair wireless services, is designed. The merit of this scheme is that, when the QoS requirements are feasible, they will be achieved with minimum energy consumption. Results of extensive simulation experiments are presented to show the effectiveness of the proposed schemes.
      Citation: Future Internet
      PubDate: 2019-07-16
      DOI: 10.3390/fi11070156
      Issue No: Vol. 11, No. 7 (2019)
  • Future Internet, Vol. 11, Pages 157: A Multi-Attention Network for
           Aspect-Level Sentiment Analysis

    • Authors: Qiuyue Zhang, Ran Lu
      First page: 157
      Abstract: Aspect-level sentiment analysis (ASA) aims at determining the sentiment polarity of specific aspect term with a given sentence. Recent advances in attention mechanisms suggest that attention models are useful in ASA tasks and can help identify focus words. Or combining attention mechanisms with neural networks are also common methods. However, according to the latest research, they often fail to extract text representations efficiently and to achieve interaction between aspect terms and contexts. In order to solve the complete task of ASA, this paper proposes a Multi-Attention Network (MAN) model which adopts several attention networks. This model not only preprocesses data by Bidirectional Encoder Representations from Transformers (BERT), but a number of measures have been taken. First, the MAN model utilizes the partial Transformer after transformation to obtain hidden sequence information. Second, because words in different location have different effects on aspect terms, we introduce location encoding to analyze the impact on distance from ASA tasks, then we obtain the influence of different words with aspect terms through the bidirectional attention network. From the experimental results of three datasets, we could find that the proposed model could achieve consistently superior results.
      Citation: Future Internet
      PubDate: 2019-07-16
      DOI: 10.3390/fi11070157
      Issue No: Vol. 11, No. 7 (2019)
  • Future Internet, Vol. 11, Pages 158: Distributed Uniform Streaming
           Framework: An Elastic Fog Computing Platform for Event Stream Processing
           and Platform Transparency

    • Authors: Simon Vanneste, Jens de Hoog, Thomas Huybrechts, Stig Bosmans, Reinout Eyckerman, Muddsair Sharif, Siegfried Mercelis, Peter Hellinckx
      First page: 158
      Abstract: The increase of Internet of Things devices and the rise of more computationally intense applications presents challenges for future Internet of Things architectures. We envision a future in which edge, fog, and cloud devices work together to execute future applications. Because the entire application cannot run on smaller edge or fog devices, we will need to split the application into smaller application components. These application components will send event messages to each other to create a single application from multiple application components. The execution location of the application components can be optimized to minimize the resource consumption. In this paper, we describe the Distributed Uniform Stream (DUST) framework that creates an abstraction between the application components and the middleware which is required to make the execution location transparent to the application component. We describe a real-world application that uses the DUST framework for platform transparency. Next to the DUST framework, we also describe the distributed DUST Coordinator, which will optimize the resource consumption by moving the application components to a different execution location. The coordinators will use an adapted version of the Contract Net Protocol to find local minima in resource consumption.
      Citation: Future Internet
      PubDate: 2019-07-19
      DOI: 10.3390/fi11070158
      Issue No: Vol. 11, No. 7 (2019)
  • Future Internet, Vol. 11, Pages 159: Implementation and Evaluation of
           Activity-Based Congestion Management Using P4 (P4-ABC)

    • Authors: Michael Menth, Habib Mostafaei, Daniel Merling, Marco Häberle
      First page: 159
      Abstract: Activity-Based Congestion management (ABC) is a novel domain-based QoS mechanism providing more fairness among customers on bottleneck links. It avoids per-flow or per-customer states in the core network and is suitable for application in future 5G networks. However, ABC cannot be configured on standard devices. P4 is a novel programmable data plane specification which allows defining new headers and forwarding behavior. In this work, we implement an ABC prototype using P4 and point out challenges experienced during implementation. Experimental validation of ABC using the P4-based prototype reveals the desired fairness results.
      Citation: Future Internet
      PubDate: 2019-07-19
      DOI: 10.3390/fi11070159
      Issue No: Vol. 11, No. 7 (2019)
  • Future Internet, Vol. 11, Pages 160: Crossing the Borders: Re-Use of Smart
           Learning Objects in Advanced Content Access Systems

    • Authors: Hamza Manzoor, Kamil Akhuseyinoglu, Jackson Wonderly, Peter Brusilovsky, Clifford A. Shaffer
      First page: 160
      Abstract: Researchers in many disciplines are developing novel interactive smart learning objects like exercises and visualizations. Meanwhile, Learning Management Systems (LMS) and eTextbook systems are also becoming more sophisticated in their ability to use standard protocols to make use of third party smart learning objects. But at this time, educational tool developers do not always make best use of the interoperability standards and need exemplars to guide and motivate their development efforts. In this paper we present a case study where the two large educational ecosystems use the Learning Tools Interoperability (LTI) standard to allow cross-sharing of their educational materials. At the end of our development process, Virginia Tech’s OpenDSA eTextbook system became able to import materials from Aalto University’s ACOS smart learning content server, such as python programming exercises and Parsons problems. Meanwhile, University of Pittsburgh’s Mastery Grids (which already uses the ACOS exercises) was made to support CodeWorkout programming exercises (a system already used within OpenDSA). Thus, four major projects in CS Education became inter-operable.
      Citation: Future Internet
      PubDate: 2019-07-19
      DOI: 10.3390/fi11070160
      Issue No: Vol. 11, No. 7 (2019)
  • Future Internet, Vol. 11, Pages 161: Leveraging the Internet of Things and
           Blockchain Technology in Supply Chain Management

    • Authors: Abderahman Rejeb, John G. Keogh, Horst Treiblmaier
      First page: 161
      Abstract: Modern supply chains have evolved into highly complex value networks and turned into a vital source of competitive advantage. However, it has become increasingly challenging to verify the source of raw materials and maintain visibility of products and merchandise while they are moving through the value chain network. The application of the Internet of Things (IoT) can help companies to observe, track, and monitor products, activities, and processes within their respective value chain networks. Other applications of IoT include product monitoring to optimize operations in warehousing‚ manufacturing, and transportation. In combination with IoT, Blockchain technology can enable a broad range of different application scenarios to enhance value chain transparency and to increase B2B trust. When combined, IoT and Blockchain technology have the potential to increase the effectiveness and efficiency of modern supply chains. The contribution of this paper is twofold. First, we illustrate how the deployment of Blockchain technology in combination with IoT infrastructure can streamline and benefit modern supply chains and enhance value chain networks. Second, we derive six research propositions outlining how Blockchain technology can impact key features of the IoT (i.e., scalability, security, immutability and auditing, information flows, traceability and interoperability, quality) and thus lay the foundation for future research projects.
      Citation: Future Internet
      PubDate: 2019-07-20
      DOI: 10.3390/fi11070161
      Issue No: Vol. 11, No. 7 (2019)
  • Future Internet, Vol. 11, Pages 162: Improving Forensic Triage Efficiency
           through Cyber Threat Intelligence

    • Authors: Nikolaos Serketzis, Vasilios Katos, Christos Ilioudis, Dimitrios Baltatzis, Georgios Pangalos
      First page: 162
      Abstract: The complication of information technology and the proliferation of heterogeneous security devices that produce increased volumes of data coupled with the ever-changing threat landscape challenges have an adverse impact on the efficiency of information security controls and digital forensics, as well as incident response approaches. Cyber Threat Intelligence (CTI)and forensic preparedness are the two parts of the so-called managed security services that defendants can employ to repel, mitigate or investigate security incidents. Despite their success, there is no known effort that has combined these two approaches to enhance Digital Forensic Readiness (DFR) and thus decrease the time and cost of incident response and investigation. This paper builds upon and extends a DFR model that utilises actionable CTI to improve the maturity levels of DFR. The effectiveness and applicability of this model are evaluated through a series of experiments that employ malware-related network data simulating real-world attack scenarios. To this extent, the model manages to identify the root causes of information security incidents with high accuracy (90.73%), precision (96.17%) and recall (93.61%), while managing to decrease significantly the volume of data digital forensic investigators need to examine. The contribution of this paper is twofold. First, it indicates that CTI can be employed by digital forensics processes. Second, it demonstrates and evaluates an efficient mechanism that enhances operational DFR.
      Citation: Future Internet
      PubDate: 2019-07-23
      DOI: 10.3390/fi11070162
      Issue No: Vol. 11, No. 7 (2019)
  • Future Internet, Vol. 11, Pages 163: Platform Economy and
           Techno-Regulation—Experimenting with Reputation and Nudge

    • Authors: Nicola Lettieri, Alfonso Guarino, Delfina Malandrino, Rocco Zaccagnino
      First page: 163
      Abstract: In the cloud-based society, where the vast majority of social, economic and personal interactions is mediated by information communication technology (ICT), technology is no longer simply a subject of regulation but is becoming an integral part of the regulatory process. Techno-regulation, the “intentional influencing of individuals’ behavior by building norms into technological devices,” is inspiring new ways to support legal safeguards through hardware and software tools, technical solutions allowing the creation of legal relations, hampering breaches of law and even promoting norm compliance. This paper touches on these issues by focusing on Digital Labor Platforms, one of the most relevant phenomena in the gig economy. We present a research project exploring innovative techno-regulatory solutions to protect gig economy workers. The idea is to integrate, in the same strategy, legal principles, regulatory objectives and software solutions. Our attention focuses on two results of our activity—a techno-regulatory model relying on reputational mechanisms to affect the behavior of digital labor market operators and GigAdvisor, a cross-platform experimental application implementing the model.
      Citation: Future Internet
      PubDate: 2019-07-23
      DOI: 10.3390/fi11070163
      Issue No: Vol. 11, No. 7 (2019)
  • Future Internet, Vol. 11, Pages 221: Integration of LTE 230 and LTE 1800
           in Power Wireless Private Networks

    • Authors: Ding, Miao, Zhang, Li, Liu, Zou, Xu
      First page: 221
      Abstract: Power wireless private networks (PWPNs) have been highly developed in China in recent years. They provide a basis for the energy Internet of Things, which enables the exchange of energy information between devices. Although the power wireless private network is an imitation of the public cellular network, a number of special challenges remain in power private networks. Due to the lack of general standards for PWPNs at the beginning of deployment, there are now two independent PWPN systems in China: long-term evolution (LTE) 230 and LTE 1800. Each has its own core and access networks with independent hardware. In this paper, we propose a high-level design of multinetwork integration to allow LTE 230 and LTE 1800 to coexist. For core network integration, we propose a protocol controller to select the active protocol according to the user’s mode selection, since both LTE 230 and LTE 1800 evolved from the standard LTE system. For access network integration, we propose a multinetwork integration controller to help the device access the optimal cell. The simulation results show that the integrated system can retain the advantages of these two independent systems in terms of both capacity and coverage.
      Citation: Future Internet
      PubDate: 2019-10-23
      DOI: 10.3390/fi11110221
      Issue No: Vol. 11, No. 11 (2019)
  • Future Internet, Vol. 11, Pages 222: Fog Computing in IoT Smart
           Environments via Named Data Networking: A Study on Service Orchestration

    • Authors: Marica Amadeo, Giuseppe Ruggeri, Claudia Campolo, Antonella Molinaro, Valeria Loscrí, Carlos T. Calafate
      First page: 222
      Abstract: By offering low-latency and context-aware services, fog computing will have a peculiar role in the deployment of Internet of Things (IoT) applications for smart environments. Unlike the conventional remote cloud, for which consolidated architectures and deployment options exist, many design and implementation aspects remain open when considering the latest fog computing paradigm. In this paper, we focus on the problems of dynamically discovering the processing and storage resources distributed among fog nodes and, accordingly, orchestrating them for the provisioning of IoT services for smart environments. In particular, we show how these functionalities can be effectively supported by the revolutionary Named Data Networking (NDN) paradigm. Originally conceived to support named content delivery, NDN can be extended to request and provide named computation services, with NDN nodes acting as both content routers and in-network service executors. To substantiate our analysis, we present an NDN fog computing framework with focus on a smart campus scenario, where the execution of IoT services is dynamically orchestrated and performed by NDN nodes in a distributed fashion. A simulation campaign in ndnSIM, the reference network simulator of the NDN research community, is also presented to assess the performance of our proposal against state-of-the-art solutions. Results confirm the superiority of the proposal in terms of service provisioning time, paid at the expenses of a slightly higher amount of traffic exchanged among fog nodes.
      Citation: Future Internet
      PubDate: 2019-10-24
      DOI: 10.3390/fi11110222
      Issue No: Vol. 11, No. 11 (2019)
  • Future Internet, Vol. 11, Pages 223: Operation Scheduling Optimization for
           Microgrids Considering Coordination of Their Components

    • Authors: Hirotaka Takano, Ryota Goto, Thin Zar Soe, Nguyen Duc Tuyen, Hiroshi Asano
      First page: 223
      Abstract: Operation scheduling is one of the most practical optimization problems to efficiently manage the electric power supply and demand in microgrids. Although various microgrid-related techniques have been developed, there has been no established solution to the problem until now. This is because the formulated problem becomes a complicated mixed-integer programming problem having multiple optimization variables. The authors present a framework for this problem and its effective solution to obtain an operation schedule of the microgrid components considering their coordination. In the framework, trading electricity with traditional main power grids is included in the optimization target, and uncertainty originating from variable renewable energy sources is considered. In the solution, the formulated problem is reformulated to reduce the dimensions of its solution space, and, as a result, a combined algorithm of binary particle swarm optimization and quadratic programming is applicable. Through numerical simulations and discussions of their results, the validity of the authors’ proposal is verified.
      Citation: Future Internet
      PubDate: 2019-10-24
      DOI: 10.3390/fi11110223
      Issue No: Vol. 11, No. 11 (2019)
  • Future Internet, Vol. 11, Pages 224: Impacts of Video Display on Purchase
           Intention for Digital and Home Appliance Products—Empirical Study from

    • Authors: Ruohong Hao, Bingjia Shao, Rong Ma
      First page: 224
      Abstract: Rapid online trading expansion and the bloom of internet technologies has raised the importance of effective product video presentations for online retailers. This article developed a model for the impacts of video presentations on purchase intention for digital and home appliance products. Four group experiments were designed, and empirical tests were performed. This research found that presenting videos on how to use digital and home appliance products increased purchase intention by raising the information gained by customers. Meanwhile, video tutorial information had insignificant effects related to the knowledge and experience of customers.
      Citation: Future Internet
      PubDate: 2019-10-24
      DOI: 10.3390/fi11110224
      Issue No: Vol. 11, No. 11 (2019)
  • Future Internet, Vol. 11, Pages 225: FaDe: A Blockchain-Based Fair Data
           Exchange Scheme for Big Data Sharing

    • Authors: Yuling Chen, Jinyi Guo, Changlou Li, Wei Ren
      First page: 225
      Abstract: In the big data era, data are envisioned as critical resources with various values, e.g., business intelligence, management efficiency, and financial evaluations. Data sharing is always mandatory for value exchanges and profit promotion. Currently, certain big data markets have been created for facilitating data dissemination and coordinating data transaction, but we have to assume that such centralized management of data sharing must be trustworthy for data privacy and sharing fairness, which very likely imposes limitations such as joining admission, sharing efficiency, and extra costly commissions. To avoid these weaknesses, in this paper, we propose a blockchain-based fair data exchange scheme, called FaDe. FaDe can enable de-centralized data sharing in an autonomous manner, especially guaranteeing trade fairness, sharing efficiency, data privacy, and exchanging automation. A fairness protocol based on bit commitment is proposed. An algorithm based on blockchain script architecture for a smart contract, e.g., by a bitcoin virtual machine, is also proposed and implemented. Extensive analysis justifies that the proposed scheme can guarantee data exchanging without a trusted third party fairly, efficiently, and automatically.
      Citation: Future Internet
      PubDate: 2019-10-24
      DOI: 10.3390/fi11110225
      Issue No: Vol. 11, No. 11 (2019)
  • Future Internet, Vol. 11, Pages 226: Collaborative Blockchain-Based
           Detection of Distributed Denial of Service Attacks Based on Internet of
           Things Botnets

    • Authors: Georgios Spathoulas, Nikolaos Giachoudis, Georgios-Paraskevas Damiris, Georgios Theodoridis
      First page: 226
      Abstract: Internet of Things is one of the most significant latest developments in computer science. It is common for modern computing infrastructures to partially consist of numerous low power devices that are characterized by high diversity in both hardware and software. Existing security models, approaches and solutions are not able to sufficiently protect such systems. In this paper we propose the use of lightweight agents installed at multiple internet of things (IoT) installations (e.g., smart-homes), in order to collaboratively detect distributed denial of service (DDoS) attacks conducted by the use of IoT devices botnets. Specifically, agents exchange outbound traffic information in order to identify possible victims of DDoS attacks. This information exchange is governed by a blockchain smart contract, that ensures the integrity of both the procedure and the information. A simulation of the operation of the proposed methodology has been conducted in order to evaluate both its detection efficiency and its resilience against malicious agents that aim to falsify results.
      Citation: Future Internet
      PubDate: 2019-10-25
      DOI: 10.3390/fi11110226
      Issue No: Vol. 11, No. 11 (2019)
  • Future Internet, Vol. 11, Pages 227: IoT Based Smart City Bus Stops

    • Authors: Miraal Kamal, Manal Atif, Hafsa Mujahid, Tamer Shanableh, A. R. Al-Ali, Ahmad Al Nabulsi
      First page: 227
      Abstract: The advent of smart sensors, single system-on-chip computing devices, Internet of Things (IoT), and cloud computing is facilitating the design and development of smart devices and services. These include smart meters, smart street lightings, smart gas stations, smart parking lots, and smart bus stops. Countries in the Gulf region have hot and humid weather around 6–7 months of the year, which might lead to uncomfortable conditions for public commuters. Transportation authorities have made some major enhancements to existing bus stops by installing air-conditioning units, but without any remote monitoring and control features. This paper proposes a smart IoT-based environmentally - friendly enhanced design for existing bus stop services in the United Arab Emirates. The objective of the proposed design was to optimize energy consumption through estimating bus stop occupancy, remotely monitor air conditioning and lights, automatically report utility breakdowns, and measure the air pollution around the area. In order to accomplish this, bus stops will be equipped with a WiFi-Based standalone microcontroller connected to sensors and actuators. The microcontroller transmits the sensor readings to a real-time database hosted in the cloud and incorporates a mobile app that notifies operators or maintenance personnel in the case of abnormal readings or breakdowns. The mobile app encompasses a map interface enabling operators to remotely monitor the conditions of bus stops such as the temperature, humidity, estimated occupancy, and air pollution levels. In addition to presenting the system’s architecture and detailed design, a system prototype is built to test and validate the proposed solution.
      Citation: Future Internet
      PubDate: 2019-10-26
      DOI: 10.3390/fi11110227
      Issue No: Vol. 11, No. 11 (2019)
  • Future Internet, Vol. 11, Pages 228: Special Issue “New Perspectives in
           Intelligent Transportation Systems and Mobile Communications towards a
           Smart Cities Context”

    • Authors: Giovanni Pau, Alessandro Severino, Antonino Canale
      First page: 228
      Abstract: Intelligent transportation solutions and smart information and communication technologies will be the core of future smart cities. For this purpose, these topics have captivated noteworthy interest in the investigation and construction of cleverer communication protocols or the application of artificial intelligence in the connection of in-vehicle devices by wireless networks, and in in-vehicle services for autonomous driving using high-precision positioning and sensing systems. This special issue has focused on the collection of high-quality papers aimed at solving open technical problems and challenges typical of mobile communications for Intelligent Transportation Systems.
      Citation: Future Internet
      PubDate: 2019-10-28
      DOI: 10.3390/fi11110228
      Issue No: Vol. 11, No. 11 (2019)
  • Future Internet, Vol. 11, Pages 229: Predicting Rogue Content and Arabic
           Spammers on Twitter

    • Authors: Adel R. Alharbi, Amer Aljaedi
      First page: 229
      Abstract: Twitter is one of the most popular online social networks for spreading propaganda and words in the Arab region. Spammers are now creating rogue accounts to distribute adult content through Arabic tweets that Arabic norms and cultures prohibit. Arab governments are facing a huge challenge in the detection of these accounts. Researchers have extensively studied English spam on online social networks, while to date, social network spam in other languages has been completely ignored. In our previous study, we estimated that rogue and spam content accounted for approximately three quarters of all content with Arabic trending hashtags in Saudi Arabia. This alarming rate, supported by autonomous concurrent estimates, highlights the urgent need to develop adaptive spam detection methods. In this work, we collected a pure data set from spam accounts producing Arabic tweets. We applied lightweight feature engineering based on rogue content and user profiles. The 47 generated features were analyzed, and the best features were selected. Our performance results show that the random forest classification algorithm with 16 features performs best, with accuracy rates greater than 90%.
      Citation: Future Internet
      PubDate: 2019-10-30
      DOI: 10.3390/fi11110229
      Issue No: Vol. 11, No. 11 (2019)
  • Future Internet, Vol. 11, Pages 230: High-Level Smart Decision Making of a
           Robot Based on Ontology in a Search and Rescue Scenario

    • Authors: Xiaolei Sun, Yu Zhang, Jing Chen
      First page: 230
      Abstract: The search and rescue (SAR) scenario is complex and uncertain where a robot needs to understand the scenario to make smart decisions. Aiming at the knowledge representation (KR) in the field of SAR, this paper builds an ontology model that enables a robot to understand how to make smart decisions. The ontology is divided into three parts, namely entity ontology, environment ontology, and task ontology. Web Ontology Language (OWL) is adopted to represent these three types of ontology. Through ontology and Semantic Web Rule Language (SWRL) rules, the robot infers the tasks to be performed according to the environment state and at the same time obtains the semantic information of the victims. Then, the paper proposes an ontology-based algorithm for task planning to get a sequence of atomic actions so as to complete the high-level inferred task. In addition, an indoor experiment was designed and built for the SAR scenario using a real robot platform—TurtleBot3. The correctness and usability of the ontology and the proposed methods are verified by experiments.
      Citation: Future Internet
      PubDate: 2019-10-31
      DOI: 10.3390/fi11110230
      Issue No: Vol. 11, No. 11 (2019)
  • Future Internet, Vol. 11, Pages 231: A Context-Aware Conversational Agent
           in the Rehabilitation Domain

    • Authors: Thanassis Mavropoulos, Georgios Meditskos, Spyridon Symeonidis, Eleni Kamateri, Maria Rousi, Dimitris Tzimikas, Lefteris Papageorgiou, Christos Eleftheriadis, George Adamopoulos, Stefanos Vrochidis, Ioannis Kompatsiaris
      First page: 231
      Abstract: Conversational agents are reshaping our communication environment and have the potential to inform and persuade in new and effective ways. In this paper, we present the underlying technologies and the theoretical background behind a health-care platform dedicated to supporting medical stuff and individuals with movement disabilities and to providing advanced monitoring functionalities in hospital and home surroundings. The framework implements an intelligent combination of two research areas: (1) sensor- and camera-based monitoring to collect, analyse, and interpret people behaviour and (2) natural machine–human interaction through an apprehensive virtual assistant benefiting ailing patients. In addition, the framework serves as an important assistant to caregivers and clinical experts to obtain information about the patients in an intuitive manner. The proposed approach capitalises on latest breakthroughs in computer vision, sensor management, speech recognition, natural language processing, knowledge representation, dialogue management, semantic reasoning, and speech synthesis, combining medical expertise and patient history.
      Citation: Future Internet
      PubDate: 2019-11-01
      DOI: 10.3390/fi11110231
      Issue No: Vol. 11, No. 11 (2019)
  • Future Internet, Vol. 11, Pages 232: Name-Based Security for
           Information-Centric Networking Architectures

    • Authors: Fotiou, Polyzos
      First page: 232
      Abstract: Information-Centric Networking (ICN) is an emerging communication paradigm built around content names. Securing ICN using named-based security is, therefore, a natural choice. For this paper, we designed and evaluated name-based security solutions that satisfy security requirements that are particular to ICN architectures. In order to achieve our goal, we leverage identity-based encryption, identity-based proxy re-encryption, and the emerging paradigm of decentralized identifiers. Our solutions support outsourcing content storage, content integrity protection and content authentication, and provenance verification, as well as access control. We show that our solutions have tolerable storage and computation overhead, thus proving their feasibility.
      Citation: Future Internet
      PubDate: 2019-11-01
      DOI: 10.3390/fi11110232
      Issue No: Vol. 11, No. 11 (2019)
  • Future Internet, Vol. 11, Pages 233: Research on Cooperative Communication
           Strategy and Intelligent Agent Directional Source Grouping Algorithms for
           Internet of Things

    • Authors: Zou, Zhang, Yi
      First page: 233
      Abstract: In order to improve the network layer of the Internet of things to improve transmission reliability, save time delay and energy consumption, the Internet of things cooperative communication and intelligent agent technology were studied in this paper. In cooperative communication, a new cooperative communication algorithm KCN (k-cooperative node), and a reliability prediction model are proposed. The k value is determined by the end-to-end reliability. After k cooperative nodes are selected, other nodes enter dormancy. In aggregate traffic allocation, game theory is used to model the traffic equilibrium and end-to-end delay optimization scenarios. In practice, the optimal duty cycle can be calculated, which makes some cooperative nodes enter an idle state to save energy. Under the premise of guaranteeing end-to-end delay, it is shown that the reliability of the proposed KCN algorithm is better than that of the other existing routing protocols. In the aspect of intelligent agent, a directional source grouping algorithm D-MIP is proposed. This algorithm studies the routing problem of multi-agent parallel access to multiple source nodes. A directed source packet multi-agent routing planning algorithm is proposed. The iterative algorithm of each source node is limited to a sector, and the optimal intelligent agent route is obtained by selecting an appropriate angle. Compared with other algorithms, it is shown through a lot of simulated results that energy consumption and time delay has been saved by the proposed D-MIP algorithm.
      Citation: Future Internet
      PubDate: 2019-11-01
      DOI: 10.3390/fi11110233
      Issue No: Vol. 11, No. 11 (2019)
  • Future Internet, Vol. 11, Pages 234: Toward Addressing Location Privacy
           Issues: New Affiliations with Social and Location Attributes

    • Authors: Vgena, Kitsiou, Kalloniatis, Kavroudakis, Gritzalis
      First page: 234
      Abstract: Nowadays, location-sharing applications (LSA) within social media enable users to share their location information at different levels of precision. Users on their side are willing to disclose this kind of information in order to represent themselves in a socially acceptable online way. However, they express privacy concerns regarding potential malware location-sharing applications, since users’ geolocation information can provide affiliations with their social identity attributes that enable the specification of their behavioral normativity, leading to sensitive information disclosure and privacy leaks. This paper, after a systematic review on previous social and privacy location research, explores the overlapping of these fields in identifying users’ social attributes through examining location attributes while online, and proposes a targeted set of location privacy attributes related to users’ socio-spatial characteristics within social media.
      Citation: Future Internet
      PubDate: 2019-11-01
      DOI: 10.3390/fi11110234
      Issue No: Vol. 11, No. 11 (2019)
  • Future Internet, Vol. 11, Pages 235: Edge Computing Simulators for IoT
           System Design: An Analysis of Qualities and Metrics

    • Authors: Majid Ashouri, Fabian Lorig, Paul Davidsson, Romina Spalazzese
      First page: 235
      Abstract: The deployment of Internet of Things (IoT) applications is complex since many quality characteristics should be taken into account, for example, performance, reliability, and security. In this study, we investigate to what extent the current edge computing simulators support the analysis of qualities that are relevant to IoT architects who are designing an IoT system. We first identify the quality characteristics and metrics that can be evaluated through simulation. Then, we study the available simulators in order to assess which of the identified qualities they support. The results show that while several simulation tools for edge computing have been proposed, they focus on a few qualities, such as time behavior and resource utilization. Most of the identified qualities are not considered and we suggest future directions for further investigation to provide appropriate support for IoT architects.
      Citation: Future Internet
      PubDate: 2019-11-08
      DOI: 10.3390/fi11110235
      Issue No: Vol. 11, No. 11 (2019)
  • Future Internet, Vol. 11, Pages 236: Machine Learning-Based Patient Load
           Prediction and IoT Integrated Intelligent Patient Transfer Systems

    • Authors: Kambombo Mtonga, Santhi Kumaran, Chomora Mikeka, Kayalvizhi Jayavel, Jimmy Nsenga
      First page: 236
      Abstract: A mismatch between staffing ratios and service demand leads to overcrowding of patients in waiting rooms of health centers. Overcrowding consequently leads to excessive patient waiting times, incomplete preventive service delivery and disgruntled medical staff. Worse, due to the limited patient load that a health center can handle, patients may leave the clinic before the medical examination is complete. It is true that as one health center may be struggling with an excessive patient load, another facility in the vicinity may have a low patient turn out. A centralized hospital management system, where hospitals are able to timely exchange patient load information would allow excess patient load from an overcrowded health center to be re-assigned in a timely way to the nearest health centers. In this paper, a machine learning-based patient load prediction model for forecasting future patient loads is proposed. Given current and historical patient load data as inputs, the model outputs future predicted patient loads. Furthermore, we propose re-assigning excess patient loads to nearby facilities that have minimal load as a way to control overcrowding and reduce the number of patients that leave health facilities without receiving medical care as a result of overcrowding. The re-assigning of patients will imply a need for transportation for the patient to move from one facility to another. To avoid putting a further strain on the already fragmented ambulatory services, we assume the existence of a scheduled bus system and propose an Internet of Things (IoT) integrated smart bus system. The developed IoT system can be tagged on buses and can be queried by patients through representation state transfer application program interfaces (APIs) to provide them with the position of the buses through web app or SMS relative to their origin and destination stop. The back end of the proposed system is based on message queue telemetry transport, which is lightweight, data efficient and scalable, unlike the traditionally used hypertext transfer protocol.
      Citation: Future Internet
      PubDate: 2019-11-12
      DOI: 10.3390/fi11110236
      Issue No: Vol. 11, No. 11 (2019)
  • Future Internet, Vol. 11, Pages 237: Feature Fusion Text Classification
           Model Combining CNN and BiGRU with Multi-Attention Mechanism

    • Authors: Jingren Zhang, Fang’ai Liu, Weizhi Xu, Hui Yu
      First page: 237
      Abstract: Convolutional neural networks (CNN) and long short-term memory (LSTM) have gained wide recognition in the field of natural language processing. However, due to the pre- and post-dependence of natural language structure, relying solely on CNN to implement text categorization will ignore the contextual meaning of words and bidirectional long short-term memory (BiLSTM). The feature fusion model is divided into a multiple attention (MATT) CNN model and a bi-directional gated recurrent unit (BiGRU) model. The CNN model inputs the word vector (word vector attention, part of speech attention, position attention) that has been labeled by the attention mechanism into our multi-attention mechanism CNN model. Obtaining the influence intensity of the target keyword on the sentiment polarity of the sentence, and forming the first dimension of the sentiment classification, the BiGRU model replaces the original BiLSTM and extracts the global semantic features of the sentence level to form the second dimension of sentiment classification. Then, using PCA to reduce the dimension of the two-dimensional fusion vector, we finally obtain a classification result combining two dimensions of keywords and sentences. The experimental results show that the proposed MATT-CNN+BiGRU fusion model has 5.94% and 11.01% higher classification accuracy on the MRD and SemEval2016 datasets, respectively, than the mainstream CNN+BiLSTM method.
      Citation: Future Internet
      PubDate: 2019-11-12
      DOI: 10.3390/fi11110237
      Issue No: Vol. 11, No. 11 (2019)
  • Future Internet, Vol. 11, Pages 238: Software Architecture for Mobile
           Cloud Computing Systems

    • Authors: Alreshidi, Ahmad, B. Altamimi, Sultan, Mehmood
      First page: 238
      Abstract: Mobile cloud computing (MCC) has recently emerged as a state-of-the-art technology for mobile systems. MCC enables portable and context-aware computation via mobile devices by exploiting virtually unlimited hardware and software resources offered by cloud computing servers. Software architecture helps to abstract the complexities of system design, development, and evolution phases to implement MCC systems effectively and efficiently. This paper aims to identify, taxonomically classify, and systematically map the state of the art on architecting MCC-based software. We have used an evidence-based software engineering (EBSE) approach to conduct a systematic mapping study (SMS) based on 121 qualitatively selected research studies published from 2006 to 2019. The results of the SMS highlight that architectural solutions for MCC systems are mainly focused on supporting (i) software as a service for mobile computing, (ii) off-loading mobile device data to cloud-servers, (iii) internet of things, edge, and fog computing along with various aspects like (iv) security and privacy of mobile device data. The emerging research focuses on the existing and futuristic challenges that relate to MCC-based internet of things (IoTs), mobile-cloud edge systems, along with green and energy-efficient computing. The results of the SMS facilitate knowledge transfer that could benefit researchers and practitioners to understand the role of software architecture to develop the next generation of mobile-cloud systems to support internet-driven computing.
      Citation: Future Internet
      PubDate: 2019-11-13
      DOI: 10.3390/fi11110238
      Issue No: Vol. 11, No. 11 (2019)
  • Future Internet, Vol. 11, Pages 239: Body-to-Body Cooperation in Internet
           of Medical Things: Toward Energy Efficiency Improvement

    • Authors: Dalal Abdulmohsin Hammood, Hasliza A. Rahim, Ahmed Alkhayyat, R. Badlishah Ahmad
      First page: 239
      Abstract: Internet of Medical Things (IoMT) technologies provide suitability among physicians and patients because they are useful in numerous medical fields. Wireless body sensor networks (WBSNs) are one of the most crucial technologies from within the IoMT evolution of the healthcare system, whereby each patient is monitored by low-powered and lightweight sensors. When the WBSNs are integrated into IoMT networks, they are quite likely to overlap each other; thus, cooperation between WBSN sensors is possible. In this paper, we consider communication between WBSNs and beyond their communication range. Therefore, we propose inter-WBAN cooperation for the IoMT system, which is also known as inter-WBAN cooperation in an IoMT environment (IWC-IoMT). In this paper, first, a proposed architecture for the IoT health-based system is investigated. Then, a mathematical model of the outage probability for the IWC-IoMT is derived. Finally, the energy efficiency of the IWC-IoT is analysed and inspected. The simulation and numerical results show that the IWC-IoMT (cooperative IoMT) system provides superior performance compared to the non-cooperative system.
      Citation: Future Internet
      PubDate: 2019-11-14
      DOI: 10.3390/fi11110239
      Issue No: Vol. 11, No. 11 (2019)
  • Future Internet, Vol. 11, Pages 240: Multimedia Independent Multipath
           Routing Algorithms for Internet of Things Based on a Node Hidden
           Communication Model

    • Authors: Cong Wu, Jianhui Yang
      First page: 240
      Abstract: In order to achieve a multi-path routing algorithm with time delay and energy consumption balance to alleviate the energy holes around a sink, a multimedia independent multipath routing algorithm for internet of things (IoT) based on node hidden communication model is proposed in this paper. On the premise of satisfying the application delay, a multi-source multi-path routing algorithm is proposed by using the idea of software definition and fitting multiple curves to form independent multi-path routing. Through a sink node centralized programming control source node routing, according to the priority of the source node, the dynamic angle of the source node can be allocated, which effectively reduces the energy consumption of the network. In addition, considering that the Internet of Things has more perceptive nodes, limited computing and storage capacity, frequent joining and exiting operations and other factors, a hidden communication model of nodes is designed for the IoT. It is helpful to improve the level of privacy protection in the IoT, and to effectively improve the ability of nodes to resist attacks in the IoT. The experimental results show that the proposed algorithm avoids the interference between paths and various network attacks to the greatest extent, and the energy consumption is relatively low under the requirement of quality of service (QoS) delay.
      Citation: Future Internet
      PubDate: 2019-11-15
      DOI: 10.3390/fi11110240
      Issue No: Vol. 11, No. 11 (2019)
  • Future Internet, Vol. 11, Pages 241: Reputation-Based Trust Approaches in
           Named Data Networking

    • Authors: Ioanna Angeliki Kapetanidou, Christos-Alexandros Sarros, Vassilis Tsaoussidis
      First page: 241
      Abstract: Information-Centric Networking (ICN) has arisen as an architectural solution that responds to the needs of today’s overloaded Internet, departing from the traditional host-centric access paradigm. In this paper we focus on Named Data Networking (NDN), the most prominent ICN architecture. In the NDN framework, disseminated content is at the core of the design and providing trusted content is essential. In this paper, we provide an overview of reputation-based trust approaches, present their design trade-offs and argue that these approaches can consolidate NDN trust and security by working complementary to the existing credential-based schemes. Finally, we discuss future research directions and challenges.
      Citation: Future Internet
      PubDate: 2019-11-18
      DOI: 10.3390/fi11110241
      Issue No: Vol. 11, No. 11 (2019)
  • Future Internet, Vol. 11, Pages 242: Academic Excellence, Website Quality,
           SEO Performance: Is there a Correlation'

    • Authors: Andreas Giannakoulopoulos, Nikos Konstantinou, Dimitris Koutsompolis, Minas Pergantis, Iraklis Varlamis
      First page: 242
      Abstract: The academic excellence of universities around the globe has always been a matter of extended study and so has the quality of an institution’s presence in the World Wide Web. The purpose of this research is to study the extent to which a university’s academic excellence is related to the quality of its web presence. In order to achieve this, a method was devised that quantified the website quality and search engine optimization (SEO) performance of the university websites of the top 100 universities in the Academic Ranking of World Universities (ARWU) Shanghai list. A variety of tools was employed to measure and test each website and produced a Web quality ranking, an SEO performance ranking, as well as a combined overall web ranking for each one. Comparing these rankings with the ARWU shows that academic excellence is moderately correlated with website quality, but SEO performance is not. Moreover, the overall web ranking also shows a moderate correlation with ARWU which seems to be positively influenced by website quality and negatively by SEO performance. Conclusively, the results of the research indicate that universities place particular emphasis on issues concerning website quality, while the utilization of SEO does not appear to be of equal importance, indicating possible room for improvement in this area.
      Citation: Future Internet
      PubDate: 2019-11-18
      DOI: 10.3390/fi11110242
      Issue No: Vol. 11, No. 11 (2019)
  • Future Internet, Vol. 11, Pages 243: Roll Motion Prediction of Unmanned
           Surface Vehicle Based on Coupled CNN and LSTM

    • Authors: Wenjie Zhang, Pin Wu, Yan Peng, Dongke Liu
      First page: 243
      Abstract: The prediction of roll motion in unmanned surface vehicles (USVs) is vital for marine safety and the efficiency of USV operations. However, the USV roll motion at sea is a complex time-varying nonlinear and non-stationary dynamic system, which varies with time-varying environmental disturbances as well as various sailing conditions. The conventional methods have the disadvantages of low accuracy, poor robustness, and insufficient practical application ability. The rise of deep learning provides new opportunities for USV motion modeling and prediction. In this paper, a data-driven neural network model is constructed by combining a convolution neural network (CNN) with long short-term memory (LSTM) for USV roll motion prediction. The CNN is used to extract spatially relevant and local time series features of the USV sensor data. The LSTM layer is exploited to reflect the long-term movement process of the USV and predict roll motion for the next moment. The fully connected layer is utilized to decode the LSTM output and calculate the final prediction results. The effectiveness of the proposed model was proved using USV roll motion prediction experiments based on two case studies from “JingHai-VI” and “JingHai-III” USVS of Shanghai University. Experimental results on a real data set indicated that our proposed model obviously outperformed the state-of-the-art methods.
      Citation: Future Internet
      PubDate: 2019-11-18
      DOI: 10.3390/fi11110243
      Issue No: Vol. 11, No. 11 (2019)
  • Future Internet, Vol. 11, Pages 244: Wideband Spectrum Sensing Based on
           Reconfigurable Filter Bank in Cognitive Radio

    • Authors: Wang, Wu, Yao, Qin
      First page: 244
      Abstract: In order to ease the conflict between the bandwidth demand of high-rate wireless communication and the shortage of spectrum resources, a wideband spectrum sensing method based on reconfigurable filter bank (RFB) with adjustable resolution is presented. The wideband signals are uniformly divided into multi-narrowband signals by RFB, which is designed by polyphase uniform Discrete Fourier Transform (DFT) modulation, and each sub-band is sensed by energy detection. According to the idle proportion of detected sub-bands, the number of RFB sub-bands is reset in next spectrum-sensing time. By simulating with collected wideband dataset, the influence of filter bank sub-bands number and idle state proportion on the sensing results is analyzed, and then on the basis of the trade-off between spectrum-sensing resolution and computational complexity, the optimal sub-bands number of filter bank is selected, so as to improve the detection performance and save resources.
      Citation: Future Internet
      PubDate: 2019-11-18
      DOI: 10.3390/fi11110244
      Issue No: Vol. 11, No. 11 (2019)
  • Future Internet, Vol. 11, Pages 245: Pedestrian Attribute Recognition with
           Graph Convolutional Network in Surveillance Scenarios

    • Authors: Xiangpeng Song, Hongbin Yang, Congcong Zhou
      First page: 245
      Abstract: Pedestrian attribute recognition is to predict a set of attribute labels of the pedestrian from surveillance scenarios, which is a very challenging task for computer vision due to poor image quality, continual appearance variations, as well as diverse spatial distribution of imbalanced attributes. It is desirable to model the label dependencies between different attributes to improve the recognition performance as each pedestrian normally possesses many attributes. In this paper, we treat pedestrian attribute recognition as multi-label classification and propose a novel model based on the graph convolutional network (GCN). The model is mainly divided into two parts, we first use convolutional neural network (CNN) to extract pedestrian feature, which is a normal operation processing image in deep learning, then we transfer attribute labels to word embedding and construct a correlation matrix between labels to help GCN propagate information between nodes. This paper applies the object classifiers learned by GCN to the image representation extracted by CNN to enable the model to have the ability to be end-to-end trainable. Experiments on pedestrian attribute recognition dataset show that the approach obviously outperforms other existing state-of-the-art methods.
      Citation: Future Internet
      PubDate: 2019-11-19
      DOI: 10.3390/fi11110245
      Issue No: Vol. 11, No. 11 (2019)
  • Future Internet, Vol. 11, Pages 204: No-Reference Depth Map Quality
           Evaluation Model Based on Depth Map Edge Confidence Measurement in
           Immersive Video Applications

    • Authors: Dogan, Haddad, Ekmekcioglu, Kondoz
      First page: 204
      Abstract: When it comes to evaluating perceptual quality of digital media for overall quality of experience assessment in immersive video applications, typically two main approaches stand out: Subjective and objective quality evaluation. On one hand, subjective quality evaluation offers the best representation of perceived video quality assessed by the real viewers. On the other hand, it consumes a significant amount of time and effort, due to the involvement of real users with lengthy and laborious assessment procedures. Thus, it is essential that an objective quality evaluation model is developed. The speed-up advantage offered by an objective quality evaluation model, which can predict the quality of rendered virtual views based on the depth maps used in the rendering process, allows for faster quality assessments for immersive video applications. This is particularly important given the lack of a suitable reference or ground truth for comparing the available depth maps, especially when live content services are offered in those applications. This paper presents a no-reference depth map quality evaluation model based on a proposed depth map edge confidence measurement technique to assist with accurately estimating the quality of rendered (virtual) views in immersive multi-view video content. The model is applied for depth image-based rendering in multi-view video format, providing comparable evaluation results to those existing in the literature, and often exceeding their performance.
      Citation: Future Internet
      PubDate: 2019-09-20
      DOI: 10.3390/fi11100204
      Issue No: Vol. 11, No. 10 (2019)
  • Future Internet, Vol. 11, Pages 205: Time and Power Allocation for Energy
           Efficiency Maximization in Wireless-Powered Full-Duplex Relay Systems

    • Authors: Xin Song, Yue Ni, Xiuwei Han, Lei Qin, Li Dong
      First page: 205
      Abstract: In this paper, we propose an optimal time and power allocation scheme in a wireless power supply full-duplex (FD) relay system, where we consider the number of relay antennas in the energy harvesting stage. At the same time, the energy efficiency optimization problem of the system is structured, where optimization issues related to time allocation factors and power allocation are established. For the FD dual-antenna and the FD single-antenna energy harvesting system, energy efficiency function is proven to be a concave function over the time-switch factor, and the optimal time-switching factor is theoretically obtained using the Lambert function. Then, according to the given value range of the optimal time switching factor, the optimal power distribution scheme is obtained by analyzing the derivative function of the system energy efficiency and using the properties of the Lambert function. The time-switching factor and transmission power are optimally selected at the wireless power supply FD relay. Results reveal that the performance of energy efficiency of the dual-antenna energy harvesting at the FD relay outperforms that of the single-antenna. Moreover, our results demonstrate that FD relay systems always substantially boost the energy efficiency compared with half-duplex (HD) relay systems.
      Citation: Future Internet
      PubDate: 2019-09-20
      DOI: 10.3390/fi11100205
      Issue No: Vol. 11, No. 10 (2019)
  • Future Internet, Vol. 11, Pages 206: Adaptive Coherent Receiver Settings
           for Optimum Channel Spacing in Gridless Optical Networks

    • Authors: Ahmad Abdo, Sadok Aouini, Bilal Riaz, Naim Ben-Hamida, Claude D’Amours
      First page: 206
      Abstract: In this paper, we propose a novel circuit and system to optimize the spacing between optical channels in gridless (also called flexible-grid or elastic) networking. The method will exploit the beginning-of-life link margin by enabling the channel to operate in super-Nyquist dense wavelength division multiplexing mode. We present the work in the context of software-defined networking and high-speed optical flexible-rate transponders. The clock recovery scheme allows the mitigation of jitter by decoupling the contribution of high-jitter noise sources from the clock recovery loop. The method and associated algorithm are experimentally verified where a spectrum gain of up to 2 GHz in spacing between two channels in the Media Channel (MC) is obtained compared to conventional clocking strategies. We showed that the improvement is equivalent to increasing throughput, in a data-center interconnect scenario, by up to 300 giga-bits per second per route.
      Citation: Future Internet
      PubDate: 2019-09-25
      DOI: 10.3390/fi11100206
      Issue No: Vol. 11, No. 10 (2019)
  • Future Internet, Vol. 11, Pages 207: Threat Analysis for Smart Homes

    • Authors: Georgios Kavallieratos, Nabin Chowdhury, Sokratis Katsikas, Vasileios Gkioulos, Stephen Wolthusen
      First page: 207
      Abstract: The development and deployment of highly dynamic, cyber+connected operational environments, such as smart homes, smart cities, and smart transportation systems, is increasing. The security analysis of such dynamic environments necessitates the use of dynamic risk assessment methodologies and the modeling of dynamically changing states. In this paper, we focus on the smart home environment, where the deployment of IoT devices increase the attack surface. We examine existing dynamic risk assessment methodologies, and by leveraging a smart home reference architecture we identify the security risks of a smart home’s physical and communication viewpoints, taking into consideration also dynamic operational aspects. Further, we develop a smart home network topology generator and a graph-based attack model to study dependencies among dynamically changing states and the propagation of a malware infection.
      Citation: Future Internet
      PubDate: 2019-09-25
      DOI: 10.3390/fi11100207
      Issue No: Vol. 11, No. 10 (2019)
  • Future Internet, Vol. 11, Pages 208: Joint Optimization of
           Pico-Base-Station Density and Transmit Power for an Energy-Efficient
           Heterogeneous Cellular Network

    • Authors: Jie Yang, Ziyu Pan, Hengfei Xu, Han Hu
      First page: 208
      Abstract: Heterogeneous cellular networks (HCNs) have emerged as the primary solution for explosive data traffic. However, an increase in the number of base stations (BSs) inevitably leads to an increase in energy consumption. Energy efficiency (EE) has become a focal point in HCNs. In this paper, we apply tools from stochastic geometry to investigate and optimize the energy efficiency (EE) for a two-tier HCN. The average achievable transmission rate and the total power consumption of all the BSs in a two-tier HCN is derived, and then the EE is formulated. In order to maximize EE, a one-dimensional optimization algorithm is used to optimize picocell BS density and transmit power. Based on this, an alternating optimization method aimed at maximizing EE is proposed to jointly optimize transmit power and density of picocell BSs. Simulation results validate the accuracy of the theoretical analysis and demonstrate that the proposed joint optimization method can obviously improve EE.
      Citation: Future Internet
      PubDate: 2019-09-27
      DOI: 10.3390/fi11100208
      Issue No: Vol. 11, No. 10 (2019)
  • Future Internet, Vol. 11, Pages 209: Partitioning Convolutional Neural
           Networks to Maximize the Inference Rate on Constrained IoT Devices

    • Authors: Fabíola Martins Campos de Oliveira, Edson Borin
      First page: 209
      Abstract: Billions of devices will compose the IoT system in the next few years, generating a huge amount of data. We can use fog computing to process these data, considering that there is the possibility of overloading the network towards the cloud. In this context, deep learning can treat these data, but the memory requirements of deep neural networks may prevent them from executing on a single resource-constrained device. Furthermore, their computational requirements may yield an unfeasible execution time. In this work, we propose *dn2pciot, a new algorithm to partition neural networks for efficient distributed execution. Our algorithm can optimize the neural network inference rate or the number of communications among devices. Additionally, our algorithm accounts appropriately for the shared parameters and biases of *cnn. We investigate the inference rate maximization for the LeNet model in constrained setups. We show that the partitionings offered by popular machine learning frameworks such as TensorFlow or by the general-purpose framework METIS may produce invalid partitionings for very constrained setups. The results show that our algorithm can partition LeNet for all the proposed setups, yielding up to 38% more inferences per second than METIS.
      Citation: Future Internet
      PubDate: 2019-09-29
      DOI: 10.3390/fi11100209
      Issue No: Vol. 11, No. 10 (2019)
  • Future Internet, Vol. 11, Pages 210: About Linda Again: How Narratives and
           Group Reasoning Can Influence Conjunction Fallacy

    • Authors: Camillo Donati, Andrea Guazzini, Giorgio Gronchi, Andrea Smorti
      First page: 210
      Abstract: Conjunction fallacy (together with other systematic reasoning errors) is usually explained in terms of the dual process theory of reasoning: Biases should be ascribed to fast and automatic processes, whereas slow and deliberative processes are responsible of producing answers that are correct with respect of normative criterion. The dual process theory is related to Bruner’s distinction between narrative and paradigmatic thought: Both modes of thought can be characterized by the two different processes of reasoning. In this paper, we explore the role of Bruner’s mode of thought manipulating also the difference between group vs individual reasoning. We observed that the narrative strategy of response induces more wrong answers. However, narrative-based strategies have higher effectiveness in the case of group reasoning. Our results suggest that narrative reasoning and group reasoning may induce violations of the conjunction rule when acceptable by the verisimilitude of the story. Five models are also presented in order to predict answer correctness and strategy of reasoning using a text analysis software.
      Citation: Future Internet
      PubDate: 2019-10-08
      DOI: 10.3390/fi11100210
      Issue No: Vol. 11, No. 10 (2019)
  • Future Internet, Vol. 11, Pages 211: A Trustworthy Communication Hub for
           Cyber-Physical Systems

    • Authors: Juhani Latvakoski, Jouni Heikkinen
      First page: 211
      Abstract: The motivation for this research arises from the challenges in the trustworthy communications related operation of cyber-physical systems (CPS), especially in the energy and mobility domains. The increasing amount of distributed energy resources (DERs) of prosumers and electric vehicles requires new ways for CPS communications to enable information exchanges for smart operation in peak consumption hours and balancing power levels in the energy grids in order to lower the energy cost. The huge number of mobile appliances and the related service providers do not serve properly the privacy of the owners, owing to the vertical silo type of operating model in industries. As the results of this research, we provide a trustworthy communication hub for CPS (CPS hub) for solving the challenges related to trustworthy communications between physical resources owned by different stakeholders. The CPS hub realizes the communication spaces concept, and enables combined trust and communications processes when dynamic resources owned by different stakeholders are exchanging information. The evaluations showed that the provided CPS hub enable information exchanges between distributed energy resources of different stakeholders, so that they can join the aggregation process for more flexible and efficient resource usage in energy markets. The CPS hub enable interaction between heterogeneous physical devices of multiple stakeholders to exchange information so that, for example, authorities can see the situation in the emergency area and, simultaneously, the policies of the owners can be taken into concern. Despite limited evaluation scenarios, it is shown that consideration of the ownership issues in the trustworthy communication for information exchanges between heterogeneous physical resources (devices) is possible and feasible. Several future research items, such as, for example, scalability; real-time and streams based operation; as well as consideration of the security, privacy, trust, and safety challenges, were detected. However, the evaluations showed that the constructed CPS hub contribute a set of very essential technical enablers for future smart CPS systems and create strong a basis for such future research towards a future smart society.
      Citation: Future Internet
      PubDate: 2019-10-08
      DOI: 10.3390/fi11100211
      Issue No: Vol. 11, No. 10 (2019)
  • Future Internet, Vol. 11, Pages 212: Low Delay Inter-Packet Coding in
           Vehicular Networks

    • Authors: Irina Bocharova, Boris Kudryashov, Nikita Lyamin, Erik Frick, Maben Rabi, Alexey Vinel
      First page: 212
      Abstract: In Cooperative Intelligent Transportation Systems (C-ITSs), vehicles need to wirelessly connect with Roadside units (RSUs) over limited durations when such point-to-point connections are possible. One example of such communications is the downloading of maps to the C-ITS vehicles. Another example occurs in the testing of C-ITS vehicles, where the tested vehicles upload trajectory records to the roadside units. Because of real-time requirements, and limited bandwidths, data are sent as User Datagram Protocol (UDP) packets. We propose an inter-packet error control coding scheme that improves the recovery of data when some of these packets are lost; we argue that the coding scheme has to be one of convolutional coding. We measure performance through the session averaged probability of successfully delivering groups of packets. We analyze two classes of convolution codes and propose a low-complexity decoding procedure suitable for network applications. We conclude that Reed–Solomon convolutional codes perform better than Wyner–Ash codes at the cost of higher complexity. We show this by simulation on the memoryless binary erasure channel (BEC) and channels with memory, and through simulations of the IEEE 802.11p DSRC/ITS-G5 network at the C-ITS test track AstaZero.
      Citation: Future Internet
      PubDate: 2019-10-11
      DOI: 10.3390/fi11100212
      Issue No: Vol. 11, No. 10 (2019)
  • Future Internet, Vol. 11, Pages 213: Blockchain Technology for Intelligent

    • Authors: Spyros Voulgaris, Nikos Fotiou, Vasilios A. Siris, George C. Polyzos, Mikael Jaatinen, Yannis Oikonomidis
      First page: 213
      Abstract: In the last few years, we have been witnessing the convergence of the physical with the digital world. The Internet of Things (IoT) is progressing at a fast pace, and IoT devices are becoming pervasive in our physical environments, bringing the vision of Intelligent Environments closer to reality. At the same time, the newly-introduced blockchain technology is offering for the first time ever cryptographically proven trust based on a set of mutually untrusted nodes. Blockchain technology thus has the potential to become a key component of many IoT systems, offering them an unprecedented level of accountability, transparency, and reliability. This paper first lays out the principles on which blockchain systems are operating, along with descriptions of the most noteworthy blockchain implementations. It then presents a number of systems through which blockchains may interact with external systems and third-party data sources. Finally, it provides a survey of the state-of-the-art blockchain-based systems targeting IoT applications.
      Citation: Future Internet
      PubDate: 2019-10-11
      DOI: 10.3390/fi11100213
      Issue No: Vol. 11, No. 10 (2019)
  • Future Internet, Vol. 11, Pages 214: Beam Training for Millimeter-Wave
           Communication Based on Tabu Table Enhanced Rosenbrock Algorithm

    • Authors: Li, Sun, Jiang
      First page: 214
      Abstract: The codebook-based beamforming for millimeter-wave (mm Wave) communication systems is usually used to compensate the severe attenuation of the mm Wave region. The beam training process based on pre-specified beam codebooks is considered a global optimization problem in 2-D planes formed by the potential beam index. The Rosenbrock algorithm (RA) is adopted to implement optimum beam searching whereas the simulated annealing (SA) algorithm is used to solve the problem of falling into the local optimum, due to the unavailable gradient information of the objective function. However, the RA implements rounding to the integer which leads to the problem of repeated search and beam space discontinuity caused by beam index will impair the powerful local search ability. Thus, in this paper, an enhanced RA based on tabu search and combined with SA algorithm is proposed as an alternative solution for beam search success rate. The proposed algorithm reduces the search times by forbidding the repeat search with tabu table and design of neighbor region. Moreover, to prevent the search failure, the search candidate index is defined to keep the local search ability of the original algorithm and wrap around of beam index is applied to maintain continuity of the search direction. Experimental simulations show that the proposed technique can improve the search efficiency in terms of reduced steps and increase search success rate during the beam training procedure compared to existing techniques.
      Citation: Future Internet
      PubDate: 2019-10-12
      DOI: 10.3390/fi11100214
      Issue No: Vol. 11, No. 10 (2019)
  • Future Internet, Vol. 11, Pages 215: Sensorial Network Framework Embedded
           in Ubiquitous Mobile Devices

    • Authors: Behan, Krejcar, Sabbah, Selamat
      First page: 215
      Abstract: : Today’s digital society is interconnected and networked, with modern smart devices ubiquitously built into and embedded within smart environments and other environments, where people (their users) typically live. It is very important to mention that sensorial awareness of an environment depends on one’s current location and equipment, as well as the equipment’s real-time capabilities. Personal sensorial information is considered to be the key factor for progress in the improvement of the productivity of everyday life and creation of a smart surrounding environment. This paper describes the design, implementation, and testing process of a new sensorial framework based on the current possibilities created by ubiquitous smart mobile devices with sensors, which involves computing power and battery power issues. The two parts of the proposed framework have been designed, implemented, and tested. The client part is represented by a front-end mobile application, and the back-end part is represented by a server-side application. The analysis of the data, captured during the testing phase, involves the analysis of the processing time, battery consumption, and transmitted data amount. This analysis reveals that Transmission Control Protocol (TCP) and user datagram protocol (UDP) protocols have a comparable performance, although TCP is preferable for use in local networks. In comparison to other solutions such as MobiSense or Feel the World framework, the final solution of the proposed and developed sensorial framework has two main capabilities, which are the security support and social networking possibilities. The advantage of the MobiSense platform is the existence of several real-world applications, whereas the proposed sensorial framework needs to be verified in the massive context of many users in real time.
      Citation: Future Internet
      PubDate: 2019-10-14
      DOI: 10.3390/fi11100215
      Issue No: Vol. 11, No. 10 (2019)
  • Future Internet, Vol. 11, Pages 216: A Survey on LoRaWAN Architecture,
           Protocol and Technologies

    • Authors: Mehmet Ali Ertürk, Muhammed Ali Aydın, Muhammet Talha Büyükakkaşlar, Hayrettin Evirgen
      First page: 216
      Abstract: Internet of Things (IoT) expansion led the market to find alternative communication technologies since existing protocols are insufficient in terms of coverage, energy consumption to fit IoT needs. Low Power Wide Area Networks (LPWAN) emerged as an alternative cost-effective communication technology for the IoT market. LoRaWAN is an open LPWAN standard developed by LoRa Alliance and has key features i.e., low energy consumption, long-range communication, builtin security, GPS-free positioning. In this paper, we will introduce LoRaWAN technology, the state of art studies in the literature and provide open opportunities.
      Citation: Future Internet
      PubDate: 2019-10-17
      DOI: 10.3390/fi11100216
      Issue No: Vol. 11, No. 10 (2019)
  • Future Internet, Vol. 11, Pages 217: 5G V2X System-Level Architecture of
           5GCAR Project

    • Authors: Condoluci, Gallo, Mussot, Kousaridas, Spapis, Mahlouji, Mahmoodi
      First page: 217
      Abstract: One of the goals of the 5G Communication Automotive Research and innovation (5GCAR) project has been to evaluate and propose system architecture enhancements aiming at supporting the strict requirements of vehicle-to-everything (V2X) use cases. In this paper, we provide an overview of 3GPP 5G system architecture, which is used as a baseline architecture in the project, and we present the main architectural enhancements introduced by 5GCAR. The work of the project focused on the following categories: (i) end-to-end security, also including aspects of privacy; (ii) network orchestration and management; (iii) network procedures; (iv) edge computing enhancements; and (v) multi-connectivity cooperation. The enhancements introduced by 5GCAR to above-listed categories are discussed in this paper, while a more detailed analysis of some selected features is presented.
      Citation: Future Internet
      PubDate: 2019-10-19
      DOI: 10.3390/fi11100217
      Issue No: Vol. 11, No. 10 (2019)
  • Future Internet, Vol. 11, Pages 218: Simulation-Based Performance

    • Authors: Johannes Kölsch, Christopher Heinz, Axel Ratzke, Christoph Grimm
      First page: 218
      Abstract: IoT systems consist of Hardware/Software systems (e.g., sensors) that are embedded in a physical world, networked and that interact with complex software platforms. The validation of such systems is a challenge and currently mostly done by prototypes. This paper presents the virtual environment for simulation, emulation and validation of an IoT platform and its semantic model in real life scenarios. It is based on a decentralized, bottom up approach that offers interoperability of IoT devices and the value-added services they want to use across different domains. The framework is demonstrated by a comprehensive case study. The example consists of the complete IoT “Smart Energy” use case with focus on data privacy by homomorphic encryption. The performance of the network is compared while using partially homomorphic encryption, fully homomorphic encryption and no encryption at all.As a major result, we found that our framework is capable of simulating big IoT networks and the overhead introduced by homomorphic encryption is feasible for VICINITY.
      Citation: Future Internet
      PubDate: 2019-10-22
      DOI: 10.3390/fi11100218
      Issue No: Vol. 11, No. 10 (2019)
  • Future Internet, Vol. 11, Pages 219: Assessing the Techno-Economic
           Benefits of Flexible Demand Resources Scheduling for Renewable
           Energy–Based Smart Microgrid Planning

    • Authors: Mark Kipngetich Kiptoo, Oludamilare Bode Adewuyi, Mohammed Elsayed Lotfy, Theophilus Amara, Keifa Vamba Konneh, Tomonobu Senjyu
      First page: 219
      Abstract: The need for innovative pathways for future zero-emission and sustainable power development has recently accelerated the uptake of variable renewable energy resources (VREs). However, integration of VREs such as photovoltaic and wind generators requires the right approaches to design and operational planning towards coping with the fluctuating outputs. This paper investigates the technical and economic prospects of scheduling flexible demand resources (FDRs) in optimal configuration planning of VRE-based microgrids. The proposed demand-side management (DSM) strategy considers short-term power generation forecast to efficiently schedule the FDRs ahead of time in order to minimize the gap between generation and load demand. The objective is to determine the optimal size of the battery energy storage, photovoltaic and wind systems at minimum total investment costs. Two simulation scenarios, without and with the consideration of DSM, were investigated. The random forest algorithm implemented on scikit-learn python environment is utilized for short-term power prediction, and mixed integer linear programming (MILP) on MATLAB® is used for optimum configuration optimization. From the simulation results obtained here, the application of FDR scheduling resulted in a significant cost saving of investment costs. Moreover, the proposed approach demonstrated the effectiveness of the FDR in minimizing the mismatch between the generation and load demand.
      Citation: Future Internet
      PubDate: 2019-10-22
      DOI: 10.3390/fi11100219
      Issue No: Vol. 11, No. 10 (2019)
  • Future Internet, Vol. 11, Pages 220: Blockchain and the Tokenization of
           the Individual: Societal Implications

    • Authors: Monique J. Morrow, Mehran Zarrebini
      First page: 220
      Abstract: We are living in a world where the very systems upon which trust is based are being challenged by new and exciting paradigm shifts. Centralization whether in the form of governments, financial institutions, enterprises and organizations is simply being challenged because of the lack of trust associated with data governance often experienced in the form of data breaches or simply a monetization of our data without our permission and/or incentives to participate in this emerging decentralization of structures. We see this trust deficit challenging the very institutions we have depended on including but not limited to financial institutions, private enterprises or government bodies. A new “social contract” is required as we continuously evolve into more decentralized and self-governing (or semi self-governing) entities. We will see more development in digital sovereignty with the caveat that a governance model will need to be defined. This position paper will present evidence that supports the premise that blockchain and individual tokenization could provide a new social contract.
      Citation: Future Internet
      PubDate: 2019-10-22
      DOI: 10.3390/fi11100220
      Issue No: Vol. 11, No. 10 (2019)
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