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Future Internet
Journal Prestige (SJR): 0.219
Citation Impact (citeScore): 1
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  This is an Open Access Journal Open Access journal
ISSN (Print) 1999-5903
Published by MDPI Homepage  [205 journals]
  • Future Internet, Vol. 11, Pages 8: An Agent Based Model to Analyze the
           Bitcoin Mining Activity and a Comparison with the Gold Mining Industry

    • Authors: Luisanna Cocco, Roberto Tonelli, Michele Marchesi
      First page: 8
      Abstract: In this paper, we present an analysis of the mining process of two popular assets, Bitcoin and gold. The analysis highlights that Bitcoin, more specifically its underlying technology, is a “safe haven” that allows facing the modern environmental challenges better than gold. Our analysis emphasizes that crypto-currencies systems have a social and economic impact much smaller than that of the traditional financial systems. We present an analysis of the several stages needed to produce an ounce of gold and an artificial agent-based market model simulating the Bitcoin mining process and allowing the quantification of Bitcoin mining costs. In this market model, miners validate the Bitcoin transactions using the proof of work as the consensus mechanism, get a reward in Bitcoins, sell a fraction of them to cover their expenses, and stay competitive in the market by buying and divesting hardware units and adjusting their expenses by turning off/on their machines according to the signals provided by a technical analysis indicator, the so-called relative strength index.
      Citation: Future Internet
      PubDate: 2019-01-02
      DOI: 10.3390/fi11010008
      Issue No: Vol. 11, No. 1 (2019)
  • Future Internet, Vol. 11, Pages 9: Object Detection Network Based on
           Feature Fusion and Attention Mechanism

    • Authors: Ying Zhang, Yimin Chen, Chen Huang, Mingke Gao
      First page: 9
      Abstract: In recent years, almost all of the current top-performing object detection networks use CNN (convolutional neural networks) features. State-of-the-art object detection networks depend on CNN features. In this work, we add feature fusion in the object detection network to obtain a better CNN feature, which incorporates well deep, but semantic, and shallow, but high-resolution, CNN features, thus improving the performance of a small object. Also, the attention mechanism was applied to our object detection network, AF R-CNN (attention mechanism and convolution feature fusion based object detection), to enhance the impact of significant features and weaken background interference. Our AF R-CNN is a single end to end network. We choose the pre-trained network, VGG-16, to extract CNN features. Our detection network is trained on the dataset, PASCAL VOC 2007 and 2012. Empirical evaluation of the PASCAL VOC 2007 dataset demonstrates the effectiveness and improvement of our approach. Our AF R-CNN achieves an object detection accuracy of 75.9% on PASCAL VOC 2007, six points higher than Faster R-CNN.
      Citation: Future Internet
      PubDate: 2019-01-02
      DOI: 10.3390/fi11010009
      Issue No: Vol. 11, No. 1 (2019)
  • Future Internet, Vol. 11, Pages 10: THBase: A Coprocessor-Based Scheme for
           Big Trajectory Data Management

    • Authors: Jiwei Qin, Liangli Ma, Jinghua Niu
      First page: 10
      Abstract: The rapid development of distributed technology has made it possible to store and query massive trajectory data. As a result, a variety of schemes for big trajectory data management have been proposed. However, the factor of data transmission is not considered in most of these, resulting in a certain impact on query efficiency. In view of that, we present THBase, a coprocessor-based scheme for big trajectory data management in HBase. THBase introduces a segment-based data model and a moving-object-based partition model to solve massive trajectory data storage, and exploits a hybrid local secondary index structure based on Observer coprocessor to accelerate spatiotemporal queries. Furthermore, it adopts certain maintenance strategies to ensure the colocation of relevant data. Based on these, THBase designs node-locality-based parallel query algorithms by Endpoint coprocessor to reduce the overhead caused by data transmission, thus ensuring efficient query performance. Experiments on datasets of ship trajectory show that our schemes can significantly outperform other schemes.
      Citation: Future Internet
      PubDate: 2019-01-03
      DOI: 10.3390/fi11010010
      Issue No: Vol. 11, No. 1 (2019)
  • Future Internet, Vol. 11, Pages 11: Application of a Non-Immersive VR, IoT
           Based Approach to Help Moroccan Students Carry Out Practical Activities in
           a Personal Learning Style

    • Authors: Mohamed Fahim, Brahim Ouchao, Abdeslam Jakimi, Lahcen El Bermi
      First page: 11
      Abstract: In the last few years, the evolution of new Information and Communication Technologies (ICT) and networks has enabled the appearance and development of several platforms and tools that serve to operate and distribute the learning content. In some particular domains, especially the scientific one, learners need to work on practical activities, using specific products and equipment to complete, consolidate, or verify their conceptual acquisitions. However, facing the increasing number of learners in Moroccan institutions, it becomes hard and expensive for developing countries, like Morocco, to ensure the appropriate conditions for each learner to perform such activities. The majority of the suggested platforms and tools cannot solve this issue, because of their inefficiency regarding offering students good interactive practical activities. Virtual Reality (VR) and the Internet of Things (IoT), as the two most incredible technologies of the last few decades, can be used as an alternative to create a virtual environment where the learner can carry out practical activities like in the real world. In such an environment, learners interact with both virtual and physical objects. In this research paper, we propose a new approach based on VR and IoT to enhance learning by providing learners with an educational space where they can perform some practical activities. The hybrid proposed approach has been used to create a virtual environment where learners (the final year of high school) can measure ultrasonic velocity in the air. The evaluation results show that the manipulation and coupling of real objects with virtual 3D objects increases in a striking way the learning outcomes of learners, as this allows them to feel linked to the real context.
      Citation: Future Internet
      PubDate: 2019-01-04
      DOI: 10.3390/fi11010011
      Issue No: Vol. 11, No. 1 (2019)
  • Future Internet, Vol. 11, Pages 12: Joint Uplink and Downlink Resource
           Allocation for D2D Communications System

    • Authors: Xin Song, Xiuwei Han, Yue Ni, Li Dong, Lei Qin
      First page: 12
      Abstract: In cellular networks, device-to-device communications can increase the spectrum efficiency, but some conventional schemes only consider uplink or downlink resource allocation. In this paper, we propose the joint uplink and downlink resource allocation scheme which maximizes the system capacity and guarantees the signal-to-noise-and-interference ratio of both cellular users and device-to-device pairs. The optimization problem is formulated as a mixed integer nonlinear problem that is usually NP hard. To achieve the reasonable resource allocation, the optimization problem is divided into two sub-problems including power allocation and channel assignment. It is proved that the objective function of power control is a convex function, in which the optimal transmission power can be obtained. The Hungarian algorithm is developed to achieve joint uplink and downlink channel assignment. The proposed scheme can improve the system capacity performance and increase the spectrum efficiency. Numerical results reveal that the performance of the proposed scheme of jointly uplink and downlink is better than that of the schemes for independent allocation.
      Citation: Future Internet
      PubDate: 2019-01-06
      DOI: 10.3390/fi11010012
      Issue No: Vol. 11, No. 1 (2019)
  • Future Internet, Vol. 11, Pages 13: A Crowdsensing Platform for Monitoring
           of Vehicular Emissions: A Smart City Perspective

    • Authors: Marianne Silva, Gabriel Signoretti, Julio Oliveira, Ivanovitch Silva, Daniel G. Costa
      First page: 13
      Abstract: Historically, cities follow reactive planning models where managers make decisions as problems occur. On the other hand, the exponential growth of Information and Communication Technologies (ICT) has allowed the connection of a diverse array of sensors, devices, systems, and objects. These objects can then generate data that can be transformed into information and used in a more efficient urban planning paradigm, one that allows decisions to be made before the occurrence of problems and emergencies. Therefore, this article aims to propose a platform capable of estimating the amount of carbon dioxide based on sensor readings in vehicles, indirectly contributing to a more proactive city planning based on the monitoring of vehicular pollution. Crowdsensing techniques and an On-Board Diagnostic (OBD-II) reader are used to extract data from vehicles in real time, which are then stored locally on the devices used to perform data collection. With the performed experiments, it was possible to extract information about the operation of the vehicles and their dynamics when moving in a city, providing valuable information that can support auxiliary tools for the management of urban centers.
      Citation: Future Internet
      PubDate: 2019-01-08
      DOI: 10.3390/fi11010013
      Issue No: Vol. 11, No. 1 (2019)
  • Future Internet, Vol. 11, Pages 14: Acknowledgement to Reviewers of Future
           Internet in 2018

    • Authors: Future Internet Editorial Office
      First page: 14
      Abstract: Rigorous peer-review is the corner-stone of high-quality academic publishing [...]
      Citation: Future Internet
      PubDate: 2019-01-10
      DOI: 10.3390/fi11010014
      Issue No: Vol. 11, No. 1 (2019)
  • Future Internet, Vol. 11, Pages 15: Multi-Topology Routing Algorithms in
           SDN-Based Space Information Networks

    • Authors: Xiangli Meng, Lingda Wu, Shaobo Yu
      First page: 15
      Abstract: Aiming at the complex structure of the space information networks (SIN) and the dynamic change of network topology, in order to design an efficient routing strategy, this paper establishes a SIN management architecture based on Software-defined Networking (SDN). A routing algorithm flow of the spatial information network based on a snapshot sequence is designed. For different spatial tasks with different Quality of Service (QoS) requirements, the concept of integrated link weight is proposed. The Warshall–Floyd algorithm is used to design the optimal routing strategy. A Task-oriented Bandwidth Resource Allocation (TBA) algorithm is proposed for multiple spatial tasks in the same link. Simulation results show that the algorithm can effectively guarantee the priority transmission of important tasks and avoid the unnecessary waste of bandwidth resources.
      Citation: Future Internet
      PubDate: 2019-01-12
      DOI: 10.3390/fi11010015
      Issue No: Vol. 11, No. 1 (2019)
  • Future Internet, Vol. 11, Pages 16: MAC Layer Protocols for Internet of
           Things: A Survey

    • Authors: Luiz Oliveira, Joel J. P. C. Rodrigues, Sergei A. Kozlov, Ricardo A. L. Rabêlo, Victor Hugo C. de Albuquerque
      First page: 16
      Abstract: Due to the wide variety of uses and the diversity of features required to meet an application, Internet of Things (IoT) technologies are moving forward at a strong pace to meet this demand while at the same time trying to meet the time-to-market of these applications. The characteristics required by applications, such as coverage area, scalability, transmission data rate, and applicability, refer to the Physical and Medium Access Control (MAC) layer designs of protocols. This paper presents a deep study of medium access control (MAC) layer protocols that are used in IoT with a detailed description of such protocols grouped (by short and long distance coverage). For short range coverage protocols, the following are considered: Radio Frequency Identification (RFID), Near Field Communication (NFC), Bluetooth IEEE 802.15.1, Bluetooth Low Energy, IEEE 802.15.4, Wireless Highway Addressable Remote Transducer Protocol (Wireless-HART), Z-Wave, Weightless, and IEEE 802.11 a/b/g/n/ah. For the long range group, Narrow Band IoT (NB-IoT), Long Term Evolution (LTE) CAT-0, LTE CAT-M, LTE CAT-N, Long Range Protocol (LoRa), and SigFox protocols are studied. A comparative study is performed for each group of protocols in order to provide insights and a reference study for IoT applications, considering their characteristics, limitations, and behavior. Open research issues on the topic are also identified.
      Citation: Future Internet
      PubDate: 2019-01-14
      DOI: 10.3390/fi11010016
      Issue No: Vol. 11, No. 1 (2019)
  • Future Internet, Vol. 11, Pages 17: Forward-Looking Element Recognition
           Based on the LSTM-CRF Model with the Integrity Algorithm

    • Authors: Dong Xu, Ruping Ge, Zhihua Niu
      First page: 17
      Abstract: A state-of-the-art entity recognition system relies on deep learning under data-driven conditions. In this paper, we combine deep learning with linguistic features and propose the long short-term memory-conditional random field model (LSTM-CRF model) with the integrity algorithm. This approach is primarily based on the use of part-of-speech (POS) syntactic rules to correct the boundaries of LSTM-CRF model annotations and improve its performance by raising the integrity of the elements. The method incorporates the advantages of the data-driven method and dependency syntax, and improves the precision rate of the elements without losing recall rate. Experiments show that the integrity algorithm is not only easy to combine with the other neural network model, but the overall effect is better than several advanced methods. In addition, we conducted cross-domain experiments based on a multi-industry corpus in the financial field. The results indicate that the method can be applied to other industries.
      Citation: Future Internet
      PubDate: 2019-01-14
      DOI: 10.3390/fi11010017
      Issue No: Vol. 11, No. 1 (2019)
  • Future Internet, Vol. 11, Pages 18: Adaptive Downward/Upward Routing
           Protocol for Mobile-Sensor Networks

    • Authors: Jinpeng Wang, Gérard Chalhoub, Michel Misson
      First page: 18
      Abstract: Recently, mobility support has become an important requirement in various Wireless Sensor Networks (WSNs). Low-power and Lossy Networks (LLNs) are a special type of WSNs that tolerate a certain degree of packet loss. However, due to the strict resource constraints in the computation, energy, and memory of LLNs, most routing protocols only support static network topologies. Data collection and data dissemination are two basic traffic modes in LLNs. Unlike data collection, data dissemination is less investigated in LLNs. There are two sorts of data-dissemination methods: point-to-multipoint and point-to-point. In this paper, we focus on the point-to-point method, which requires the source node to build routes to reach the destination node. We propose an adaptive routing protocol that integrates together point-to-point traffic and data-collection traffic, and supports highly mobile scenarios. This protocol quickly reacts to the movement of nodes to make faster decisions for the next-hop selection in data collection and dynamically build routes for point-to-point traffic. Results obtained through simulation show that our work outperforms two generic ad hoc routing protocols AODV and flooding on different performance metrics. Results also show the efficiency of our work in highly mobile scenarios with multiple traffic patterns.
      Citation: Future Internet
      PubDate: 2019-01-15
      DOI: 10.3390/fi11010018
      Issue No: Vol. 11, No. 1 (2019)
  • Future Internet, Vol. 11, Pages 19: A Reinforcement Learning Based
           Intercell Interference Coordination in LTE Networks

    • Authors: Djorwé Témoa, Anna Förster, Kolyang, Serge Doka Yamigno
      First page: 19
      Abstract: Long Term Evolution networks, which are cellular networks, are subject to many impairments due to the nature of the transmission channel used, i.e. the air. Intercell interference is the main impairment faced by Long Term Evolution networks as it uses frequency reuse one scheme, where the whole bandwidth is used in each cell. In this paper, we propose a full dynamic intercell interference coordination scheme with no bandwidth partitioning for downlink Long Term Evolution networks. We use a reinforcement learning approach. The proposed scheme is a joint resource allocation and power allocation scheme and its purpose is to minimize intercell interference in Long Term Evolution networks. Performances of proposed scheme shows quality of service improvement in terms of SINR, packet loss and delay compared to other algorithms.
      Citation: Future Internet
      PubDate: 2019-01-17
      DOI: 10.3390/fi11010019
      Issue No: Vol. 11, No. 1 (2019)
  • Future Internet, Vol. 11, Pages 20: ESCAPE: Evacuation Strategy through
           Clustering and Autonomous Operation in Public Safety Systems

    • Authors: Georgios Fragkos, Pavlos Athanasios Apostolopoulos, Eirini Eleni Tsiropoulou
      First page: 20
      Abstract: Natural disasters and terrorist attacks pose a significant threat to human society, and have stressed an urgent need for the development of comprehensive and efficient evacuation strategies. In this paper, a novel evacuation-planning mechanism is introduced to support the distributed and autonomous evacuation process within the operation of a public safety system, where the evacuees exploit the capabilities of the proposed ESCAPE service, towards making the most beneficial actions for themselves. The ESCAPE service was developed based on the principles of reinforcement learning and game theory, and is executed at two decision-making layers. Initially, evacuees are modeled as stochastic learning automata that select an evacuation route that they want to go based on its physical characteristics and past decisions during the current evacuation. Consequently, a cluster of evacuees is created per evacuation route, and the evacuees decide if they will finally evacuate through the specific evacuation route at the current time slot or not. The evacuees’ competitive behavior is modeled as a non-co-operative minority game per each specific evacuation route. A distributed and low-complexity evacuation-planning algorithm (i.e., ESCAPE) is introduced to implement both the aforementioned evacuee decision-making layers. Finally, the proposed framework is evaluated through modeling and simulation under several scenarios, and its superiority and benefits are revealed and demonstrated.
      Citation: Future Internet
      PubDate: 2019-01-17
      DOI: 10.3390/fi11010020
      Issue No: Vol. 11, No. 1 (2019)
  • Future Internet, Vol. 11, Pages 1: Broadening Understanding on Managing
           the Communication Infrastructure in Vehicular Networks: Customizing the
           Coverage Using the Delta Network

    • Authors: Cristiano M. Silva, Lucas D. Silva, Leonardo A. L. Santos, João F. M. Sarubbi, Andreas Pitsillides
      First page: 1
      Abstract: Over the past few decades, the growth of the urban population has been remarkable. Nowadays, 50% of the population lives in urban areas, and forecasts point that by 2050 this number will reach 70%. Today, 64% of all travel made is within urban environments and the total amount of urban kilometers traveled is expected to triple by 2050. Thus, seeking novel solutions for urban mobility becomes paramount for 21st century society. In this work, we discuss the performance of vehicular networks. We consider the metric Delta Network. The Delta Network characterizes the connectivity of the vehicular network through the percentage of travel time in which vehicles are connected to roadside units. This article reviews the concept of the Delta Network and extends its study through the presentation of a general heuristic based on the definition of scores to identify the areas of the road network that should receive coverage. After defining the general heuristic, we show how small changes in the score computation can generate very distinct (and interesting) patterns of coverage, each one suited to a given scenario. In order to exemplify such behavior, we propose three deployment strategies based on simply changing the computation of scores. We compare the proposed strategies to the intuitive strategy of allocating communication units at the most popular zones of the road network. Experiments show that the strategies derived from the general heuristic provide higher coverage than the intuitive strategy when using the same number of communication devices. Moreover, the resulting pattern of coverage is very interesting, with roadside units deployed a circle pattern around the traffic epicenter.
      Citation: Future Internet
      PubDate: 2018-12-20
      DOI: 10.3390/fi11010001
      Issue No: Vol. 11, No. 1 (2018)
  • Future Internet, Vol. 11, Pages 2: Harnessing machine learning for
           fiber-induced nonlinearity mitigation in long-haul coherent optical OFDM

    • Authors: Elias Giacoumidis, Yi Lin, Jinlong Wei, Ivan Aldaya, Athanasios Tsokanos, Liam P. Barry
      First page: 2
      Abstract: Coherent optical orthogonal frequency division multiplexing (CO-OFDM) has attracted a lot of interest in optical fiber communications due to its simplified digital signal processing (DSP) units, high spectral-efficiency, flexibility, and tolerance to linear impairments. However, CO-OFDM’s high peak-to-average power ratio imposes high vulnerability to fiber-induced non-linearities. DSP-based machine learning has been considered as a promising approach for fiber non-linearity compensation without sacrificing computational complexity. In this paper, we review the existing machine learning approaches for CO-OFDM in a common framework and review the progress in this area with a focus on practical aspects and comparison with benchmark DSP solutions.
      Citation: Future Internet
      PubDate: 2018-12-20
      DOI: 10.3390/fi11010002
      Issue No: Vol. 11, No. 1 (2018)
  • Future Internet, Vol. 11, Pages 3: Security Risk Analysis of LoRaWAN and
           Future Directions

    • Authors: Ismail Butun, Nuno Pereira, Mikael Gidlund
      First page: 3
      Abstract: LoRa (along with its upper layers definition—LoRaWAN) is one of the most promising Low Power Wide Area Network (LPWAN) technologies for implementing Internet of Things (IoT)-based applications. Although being a popular technology, several works in the literature have revealed vulnerabilities and risks regarding the security of LoRaWAN v1.0 (the official 1st specification draft). The LoRa-Alliance has built upon these findings and introduced several improvements in the security and architecture of LoRa. The result of these efforts resulted in LoRaWAN v1.1, released on 11 October 2017. This work aims at reviewing and clarifying the security aspects of LoRaWAN v1.1. By following ETSI guidelines, we provide a comprehensive Security Risk Analysis of the protocol and discuss several remedies to the security risks described. A threat catalog is presented, along with discussions and analysis in view of the scale, impact, and likelihood of each threat. To the best of the authors’ knowledge, this work is one of the first of its kind, by providing a detailed security risk analysis related to the latest version of LoRaWAN. Our analysis highlights important practical threats, such as end-device physical capture, rogue gateway and self-replay, which require particular attention by developers and organizations implementing LoRa networks.
      Citation: Future Internet
      PubDate: 2018-12-21
      DOI: 10.3390/fi11010003
      Issue No: Vol. 11, No. 1 (2018)
  • Future Internet, Vol. 11, Pages 4: A Real Case of Implementation of the
           Future 5G City

    • Authors: Dania Marabissi, Lorenzo Mucchi, Romano Fantacci, Maria Rita Spada, Fabio Massimiani, Andrea Fratini, Giorgio Cau, Jia Yunpeng, Lucio Fedele
      First page: 4
      Abstract: The fifth generation (5G) of wireless communication systems is considered the key technology to enable a wide range of application scenarios and the effective spreading of the smart city concept. Vertical business use cases, specifically designed for the future 5G city, will have a strong economical and social impact. For this reason, ongoing 5G field trials have to test newly deployed technologies as well as the capability of 5G to create a new digital economy. This paper describes the 5G field trial environment that was launched in Italy at the end of 2017. The aim is to evaluate the capability of the 5G network of supporting innovative services with reference to suitably designed key performance indicators and to evaluate the opportunities offered by these services. Indeed, vertical business use cases, specifically designed for the future 5G city, with a strong economic and social impact, are under implementation and will be evaluated. In particular, the paper provides a detailed description of the deployment of an actual complete integrated 5G network. It shows how 5G is effective enabling technology for a wide range of vertical business and use cases. Indeed, its flexibility allows to satisfy completely different performance requirements of real services. Some preliminary results, obtained during the first phase, are presented for a smart mobility scenario.
      Citation: Future Internet
      PubDate: 2018-12-22
      DOI: 10.3390/fi11010004
      Issue No: Vol. 11, No. 1 (2018)
  • Future Internet, Vol. 11, Pages 5: Forecasting E-Commerce Products Prices
           by Combining an Autoregressive Integrated Moving Average (ARIMA) Model and
           Google Trends Data

    • Authors: Salvatore Carta, Andrea Medda, Alessio Pili, Diego Reforgiato Recupero, Roberto Saia
      First page: 5
      Abstract: E-commerce is becoming more and more the main instrument for selling goods to the mass market. This led to a growing interest in algorithms and techniques able to predict products future prices, since they allow us to define smart systems able to improve the quality of life by suggesting more affordable goods and services. The joint use of time series, reputation and sentiment analysis clearly represents one important approach to this research issue. In this paper we present Price Probe, a suite of software tools developed to perform forecasting on products’ prices. Its primary aim is to predict the future price trend of products generating a customized forecast through the exploitation of autoregressive integrated moving average (ARIMA) model. We experimented the effectiveness of the proposed approach on one of the biggest E-commerce infrastructure in the world: Amazon. We used specific APIs and dedicated crawlers to extract and collect information about products and their related prices over time and, moreover, we extracted information from social media and Google Trends that we used as exogenous features for the ARIMA model. We fine-estimated ARIMA’s parameters and tried the different combinations of the exogenous features and noticed through experimental analysis that the presence of Google Trends information significantly improved the predictions.
      Citation: Future Internet
      PubDate: 2018-12-24
      DOI: 10.3390/fi11010005
      Issue No: Vol. 11, No. 1 (2018)
  • Future Internet, Vol. 11, Pages 6: A Framework for Improving the
           Engagement of Medical Practitioners in an E-Training Platform for
           Tuberculosis Care and Prevention

    • Authors: Syed Mustafa Ali, Ana Filomena Curralo, Maged N. Kamel Boulos, Sara Paiva
      First page: 6
      Abstract: We propose a new framework to improve the engagement of medical practitioners in a planned e-training platform for the successful identification and effective management of presumptive cases of tuberculosis (TB) in Pakistan. Our work is aligned with the World Health Organization’s TB-DOTS (Directly Observed Treatment Short-course) strategy for promoting the effective management of tuberculosis. We start by presenting previous work done at Mercy Corps Pakistan for training medical practitioners, then present the results of a recent survey we administered to a random sample of medical practitioners in Pakistan to learn about their requirements and readiness to embrace a new e-training platform and methodology. Informed by feedback from the survey, we formulated a detailed requirement analysis of the five key learning areas (or phases) that we believe are fundamental to the success of a TB e-training platform. Moreover, survey results revealed that an on-spot, on-demand, and competency-based learning tool can potentially improve the engagement of medical practitioners in the process. Building on the insights gained from the survey, we finally describe our initial UX (user experience) prototypes for phase 1, which corresponds to the identification of presumptive tuberculosis cases.
      Citation: Future Internet
      PubDate: 2018-12-28
      DOI: 10.3390/fi11010006
      Issue No: Vol. 11, No. 1 (2018)
  • Future Internet, Vol. 11, Pages 7: Layer-Wise Compressive Training for
           Convolutional Neural Networks

    • Authors: Matteo Grimaldi, Valerio Tenace, Andrea Calimera
      First page: 7
      Abstract: Convolutional Neural Networks (CNNs) are brain-inspired computational models designed to recognize patterns. Recent advances demonstrate that CNNs are able to achieve, and often exceed, human capabilities in many application domains. Made of several millions of parameters, even the simplest CNN shows large model size. This characteristic is a serious concern for the deployment on resource-constrained embedded-systems, where compression stages are needed to meet the stringent hardware constraints. In this paper, we introduce a novel accuracy-driven compressive training algorithm. It consists of a two-stage flow: first, layers are sorted by means of heuristic rules according to their significance; second, a modified stochastic gradient descent optimization is applied on less significant layers such that their representation is collapsed into a constrained subspace. Experimental results demonstrate that our approach achieves remarkable compression rates with low accuracy loss (<1%).
      Citation: Future Internet
      PubDate: 2018-12-28
      DOI: 10.3390/fi11010007
      Issue No: Vol. 11, No. 1 (2018)
  • Future Internet, Vol. 10, Pages 82: On the Security of Rotation Operation
           Based Ultra-Lightweight Authentication Protocols for RFID Systems

    • Authors: Masoumeh Safkhani, Nasour Bagheri, Mahyar Shariat
      First page: 82
      Abstract: Passive Radio Frequency IDentification (RFID) tags are generally highly constrained and cannot support conventional encryption systems to meet the required security. Hence, designers of security protocols may try to achieve the desired security only using limited ultra-lightweight operations. In this paper, we show that the security of such protocols is not provided by using rotation functions. In the following, for an example, we investigate the security of an RFID authentication protocol that has been recently developed using rotation function named ULRAS, which stands for an Ultra-Lightweight RFID Authentication Scheme and show its security weaknesses. More precisely, we show that the ULRAS protocol is vulnerable against de-synchronization attack. The given attack has the success probability of almost ‘1’, with the complexity of only one session of the protocol. In addition, we show that the given attack can be used as a traceability attack against the protocol if the parameters’ lengths are an integer power of 2, e.g., 128. Moreover, we propose a new authentication protocol named UEAP, which stands for an Ultra-lightweight Encryption based Authentication Protocol, and then informally and formally, using Scyther tool, prove that the UEAP protocol is secure against all known active and passive attacks.
      Citation: Future Internet
      PubDate: 2018-08-21
      DOI: 10.3390/fi10090082
      Issue No: Vol. 10, No. 9 (2018)
  • Future Internet, Vol. 10, Pages 83: A HMM-R Approach to Detect L-DDoS
           Attack Adaptively on SDN Controller

    • Authors: Wentao Wang, Xuan Ke, Lingxia Wang
      First page: 83
      Abstract: A data center network is vulnerable to suffer from concealed low-rate distributed denial of service (L-DDoS) attacks because its data flow has the characteristics of data flow delay, diversity, and synchronization. Several studies have proposed addressing the detection of L-DDoS attacks, most of them are only detect L-DDoS attacks at a fixed rate. These methods cause low true positive and high false positive in detecting multi-rate L-DDoS attacks. Software defined network (SDN) is a new network architecture that can centrally control the network. We use an SDN controller to collect and analyze data packets entering the data center network and calculate the Renyi entropies base on IP of data packets, and then combine them with the hidden Markov model to get a probability model HMM-R to detect L-DDoS attacks at different rates. Compared with the four common attack detection algorithms (KNN, SVM, SOM, BP), HMM-R is superior to them in terms of the true positive rate, the false positive rate, and the adaptivity.
      Citation: Future Internet
      PubDate: 2018-08-23
      DOI: 10.3390/fi10090083
      Issue No: Vol. 10, No. 9 (2018)
  • Future Internet, Vol. 10, Pages 84: Using Noise Level to Detect Frame
           Repetition Forgery in Video Frame Rate Up-Conversion

    • Authors: Yanli Li, Lala Mei, Ran Li, Changan Wu
      First page: 84
      Abstract: Frame repetition (FR) is a common temporal-domain tampering operator, which is often used to increase the frame rate of video sequences. Existing methods detect FR forgery by analyzing residual variation or similarity between video frames; however, these methods are easily interfered with by noise, affecting the stability of detection performance. This paper proposes a noise-level based detection method which detects the varying noise level over time to determine whether the video is forged by FR. Wavelet coefficients are first computed for each video frame, and median absolute deviation (MAD) of wavelet coefficients is used to estimate the standard deviation of Gaussian noise mixed in each video frame. Then, fast Fourier transform (FFT) is used to calculate the amplitude spectrum of the standard deviation curve of the video sequence, and to provide the peak-mean ratio (PMR) of the amplitude spectrum. Finally, according to the PMR obtained, a hard threshold decision is taken to determine whether the standard deviation bears periodicity in the temporal domain, in which way FR forgery can be automatically identified. The experimental results show that the proposed method ensures a large PMR for the forged video, and presents a better detection performance when compared with the existing detection methods.
      Citation: Future Internet
      PubDate: 2018-08-24
      DOI: 10.3390/fi10090084
      Issue No: Vol. 10, No. 9 (2018)
  • Future Internet, Vol. 10, Pages 85: Predictive Power Management for Wind
           Powered Wireless Sensor Node

    • Authors: Yin Wu, Bowen Li, Fuquan Zhang
      First page: 85
      Abstract: A conventional Wireless Sensor Network (WSN) cannot have an infinite lifetime without a battery recharge or replacement. Energy Harvesting (EH), from environmental energy sources, is a promising technology to provide sustainable powering for a WSN. In this paper, we propose and investigate a novel predictive energy management framework that combines the Maximal Power Transferring Tracking (MPTT) algorithm, a predictive energy allocation strategy, and a high efficiency transmission power control mechanism: First, the MPTT optimal working point guarantees minimum power loss of the EH-WSN system; Then, by exactly predicting the upcoming available energy, the power allocation strategy regulates EH-nodes’ duty cycle accurately to minimize the power failure time; Ultimately, the transmission power control module further improves energy efficiency by dynamically selecting the optimum matching transmission power level with minimum energy consumption. A wind energy powered wireless sensor system has been equipped and tested to validate the effectiveness of the proposed scheme. Results indicate that compared with other predictive energy managers, the proposed mechanism incurs relatively low power failure time while maintaining a high-energy conversion rate.
      Citation: Future Internet
      PubDate: 2018-09-06
      DOI: 10.3390/fi10090085
      Issue No: Vol. 10, No. 9 (2018)
  • Future Internet, Vol. 10, Pages 86: Sharing with Live Migration Energy
           Optimization Scheduler for Cloud Computing Data Centers

    • Authors: Samah Alshathri, Bogdan Ghita, Nathan Clarke
      First page: 86
      Abstract: The cloud-computing concept has emerged as a powerful mechanism for data storage by providing a suitable platform for data centers. Recent studies show that the energy consumption of cloud computing systems is a key issue. Therefore, we should reduce the energy consumption to satisfy performance requirements, minimize power consumption, and maximize resource utilization. This paper introduces a novel algorithm that could allocate resources in a cloud-computing environment based on an energy optimization method called Sharing with Live Migration (SLM). In this scheduler, we used the Cloud-Sim toolkit to manage the usage of virtual machines (VMs) based on a novel algorithm that learns and predicts the similarity between the tasks, and then allocates each of them to a suitable VM. On the other hand, SLM satisfies the Quality of Services (QoS) constraints of the hosted applications by adopting a migration process. The experimental results show that the algorithm exhibits better performance, while saving power and minimizing the processing time. Therefore, the SLM algorithm demonstrates improved virtual machine efficiency and resource utilization compared to an adapted state-of-the-art algorithm for a similar problem.
      Citation: Future Internet
      PubDate: 2018-09-06
      DOI: 10.3390/fi10090086
      Issue No: Vol. 10, No. 9 (2018)
  • Future Internet, Vol. 10, Pages 87: Log Likelihood Ratio Based Relay
           Selection Scheme for Amplify and Forward Relaying with Three State Markov

    • Authors: Manish Sahajwani, Alok Jain, Radheyshyam Gamad
      First page: 87
      Abstract: This paper presents log likelihood ratio (LLR) based relay selection scheme for a cooperative amplify and forward relaying system. To evaluate the performance of the aforementioned system model, a three state Markov chain based fading environment has been presented to toggle among Rayleigh, Rician, and Nakagami-m fading environment. A simulation is carried out while assuming that there is no possibility of direct transmission from the source and destination terminal. Simulation results on the basis of Bit Error Rate (BER), Instantaneous Channel Capacity, and Outage probability have been presented and compared for different cases. In each case, the best performance of the proposed algorithm is obtained with a Binary Phase Shift Keying (BPSK) modulation scheme.
      Citation: Future Internet
      PubDate: 2018-09-06
      DOI: 10.3390/fi10090087
      Issue No: Vol. 10, No. 9 (2018)
  • Future Internet, Vol. 10, Pages 88: A Systematic Literature Review on
           Military Software Defined Networks

    • Authors: Vasileios Gkioulos, Håkon Gunleifsen, Goitom Kahsay Weldehawaryat
      First page: 88
      Abstract: Software Defined Networking (SDN) is an evolving network architecture paradigm that focuses on the separation of control and data planes. SDN receives increasing attention both from academia and industry, across a multitude of application domains. In this article, we examine the current state of obtained knowledge on military SDN by conducting a systematic literature review (SLR). Through this work, we seek to evaluate the current state of the art in terms of research tracks, publications, methods, trends, and most active research areas. Accordingly, we utilize these findings for consolidating the areas of past and current research on the examined application domain, and propose directions for future research.
      Citation: Future Internet
      PubDate: 2018-09-12
      DOI: 10.3390/fi10090088
      Issue No: Vol. 10, No. 9 (2018)
  • Future Internet, Vol. 10, Pages 89: Novel Cross-View Human Action Model
           Recognition Based on the Powerful View-Invariant Features Technique

    • Authors: Sebastien Mambou, Ondrej Krejcar, Kamil Kuca, Ali Selamat
      First page: 89
      Abstract: One of the most important research topics nowadays is human action recognition, which is of significant interest to the computer vision and machine learning communities. Some of the factors that hamper it include changes in postures and shapes and the memory space and time required to gather, store, label, and process the pictures. During our research, we noted a considerable complexity to recognize human actions from different viewpoints, and this can be explained by the position and orientation of the viewer related to the position of the subject. We attempted to address this issue in this paper by learning different special view-invariant facets that are robust to view variations. Moreover, we focused on providing a solution to this challenge by exploring view-specific as well as view-shared facets utilizing a novel deep model called the sample-affinity matrix (SAM). These models can accurately determine the similarities among samples of videos in diverse angles of the camera and enable us to precisely fine-tune transfer between various views and learn more detailed shared facets found in cross-view action identification. Additionally, we proposed a novel view-invariant facets algorithm that enabled us to better comprehend the internal processes of our project. Using a series of experiments applied on INRIA Xmas Motion Acquisition Sequences (IXMAS) and the Northwestern–UCLA Multi-view Action 3D (NUMA) datasets, we were able to show that our technique performs much better than state-of-the-art techniques.
      Citation: Future Internet
      PubDate: 2018-09-13
      DOI: 10.3390/fi10090089
      Issue No: Vol. 10, No. 9 (2018)
  • Future Internet, Vol. 10, Pages 90: v-Mapper: An Application-Aware
           Resource Consolidation Scheme for Cloud Data Centers

    • Authors: Aaqif Afzaal Abbasi, Hai Jin
      First page: 90
      Abstract: Cloud computing systems are popular in computing industry for their ease of use and wide range of applications. These systems offer services that can be used over the Internet. Due to their wide popularity and usage, cloud computing systems and their services often face issues resource management related challenges. In this paper, we present v-Mapper, a resource consolidation scheme which implements network resource management concepts through software-defined networking (SDN) control features. The paper makes three major contributions: (1) We propose a virtual machine (VM) placement scheme that can effectively mitigate the VM placement issues for data-intensive applications; (2) We propose a validation scheme that will ensure that a cloud service is entertained only if there are sufficient resources available for its execution and (3) We present a scheduling policy that aims to eliminate network load constraints. We tested our scheme with other techniques in terms of average task processing time, service delay and bandwidth usage. Our results demonstrate that v-Mapper outperforms other techniques and delivers significant improvement in system’s performance.
      Citation: Future Internet
      PubDate: 2018-09-15
      DOI: 10.3390/fi10090090
      Issue No: Vol. 10, No. 9 (2018)
  • Future Internet, Vol. 10, Pages 91: Intelligent Communication in Wireless
           Sensor Networks

    • Authors: Mostefa Bendjima, Mohammed Feham
      First page: 91
      Abstract: Wireless sensor networks (WSN) are designed to collect information by means of a large number of energy-limited battery sensor nodes. Therefore, it is important to minimize the energy consumed by each sensor, in order to extend the network life. The goal of this work is to design an intelligent WSN that collects as much information as possible to process it intelligently. To achieve this goal, an agent is sent to each sensor in order to process the information and to cooperate with neighboring sensors while mobile agents (MA) can be used to reduce information shared between source nodes (SN) and send them to the base station (Sink). This work proposes to use communication architecture for wireless sensor networks based on the multi-agent system (MAS) to ensure optimal information collection. The collaboration of these agents generates a simple message that summarizes the important information in order to transmit it by a mobile agent. To reduce the size of the MA, the sensors of the network have been grouped into sectors. For each MA, we have established an optimal itinerary, consuming a minimum amount of energy with data aggregation efficiency in a minimum time. Successive simulations in large-scale wireless sensor networks through the SINALGO (published under a BSD license) simulator show the performance of the proposed method, in terms of energy consumption and package delivery rate.
      Citation: Future Internet
      PubDate: 2018-09-15
      DOI: 10.3390/fi10090091
      Issue No: Vol. 10, No. 9 (2018)
  • Future Internet, Vol. 10, Pages 68: Internet of Nano-Things, Things and
           Everything: Future Growth Trends

    • Authors: Mahdi Miraz, Maaruf Ali, Peter Excell, Richard Picking
      First page: 68
      Abstract: The current statuses and future promises of the Internet of Things (IoT), Internet of Everything (IoE) and Internet of Nano-Things (IoNT) are extensively reviewed and a summarized survey is presented. The analysis clearly distinguishes between IoT and IoE, which are wrongly considered to be the same by many commentators. After evaluating the current trends of advancement in the fields of IoT, IoE and IoNT, this paper identifies the 21 most significant current and future challenges as well as scenarios for the possible future expansion of their applications. Despite possible negative aspects of these developments, there are grounds for general optimism about the coming technologies. Certainly, many tedious tasks can be taken over by IoT devices. However, the dangers of criminal and other nefarious activities, plus those of hardware and software errors, pose major challenges that are a priority for further research. Major specific priority issues for research are identified.
      Citation: Future Internet
      PubDate: 2018-07-28
      DOI: 10.3390/fi10080068
      Issue No: Vol. 10, No. 8 (2018)
  • Future Internet, Vol. 10, Pages 69: A Watermark-Based in-Situ Access
           Control Model for Image Big Data

    • Authors: Jinyi Guo, Wei Ren, Yi Ren, Tianqin Zhu
      First page: 69
      Abstract: When large images are used for big data analysis, they impose new challenges in protecting image privacy. For example, a geographic image may consist of several sensitive areas or layers. When it is uploaded into servers, the image will be accessed by diverse subjects. Traditional access control methods regulate access privileges to a single image, and their access control strategies are stored in servers, which imposes two shortcomings: (1) fine-grained access control is not guaranteed for areas/layers in a single image that need to maintain secret for different roles; and (2) access control policies that are stored in servers suffers from multiple attacks (e.g., transferring attacks). In this paper, we propose a novel watermark-based access control model in which access control policies are associated with objects being accessed (called an in-situ model). The proposed model integrates access control policies as watermarks within images, without relying on the availability of servers or connecting networks. The access control for images is still maintained even though images are redistributed again to further subjects. Therefore, access control policies can be delivered together with the big data of images. Moreover, we propose a hierarchical key-role-area model for fine-grained encryption, especially for large size images such as geographic maps. The extensive analysis justifies the security and performance of the proposed model
      Citation: Future Internet
      PubDate: 2018-07-29
      DOI: 10.3390/fi10080069
      Issue No: Vol. 10, No. 8 (2018)
  • Future Internet, Vol. 10, Pages 70: Multidiscipline Integrated Platform
           Based on Probabilistic Analysis for Manufacturing Engineering Processes

    • Authors: Lijun Zhang, Kai Liu, Jian Liu
      First page: 70
      Abstract: Researchers from different disciplines, such as materials science, computer science, safety science, mechanical engineering and controlling engineering, have aimed to improve the quality of manufacturing engineering processes. Considering the requirements of research and development of advanced materials, reliable manufacturing and collaborative innovation, a multidiscipline integrated platform framework based on probabilistic analysis for manufacturing engineering processes is proposed. The proposed platform consists of three logical layers: The requirement layer, the database layer and the application layer. The platform is intended to be a scalable system to gradually supplement related data, models and approaches. The main key technologies of the platform, encapsulation methods, information fusion approaches and the collaborative mechanism are also discussed. The proposed platform will also be gradually improved in the future. In order to exchange information for manufacturing engineering processes, scientists and engineers of different institutes of materials science and manufacturing engineering should strengthen their cooperation.
      Citation: Future Internet
      PubDate: 2018-07-30
      DOI: 10.3390/fi10080070
      Issue No: Vol. 10, No. 8 (2018)
  • Future Internet, Vol. 10, Pages 71: Hybrid Approach with Improved Genetic
           Algorithm and Simulated Annealing for Thesis Sampling

    • Authors: Shardrom Johnson, Jinwu Han, Yuanchen Liu, Li Chen, Xinlin Wu
      First page: 71
      Abstract: Sampling inspection uses the sample characteristics to estimate that of the population, and it is an important method to describe the population, which has the features of low cost, strong applicability and high scientificity. This paper aims at the sampling inspection of the master’s degree thesis to ensure their quality, which is commonly estimated by random sampling. Since there are disadvantages in random sampling, a hybrid algorithm combined with an improved genetic algorithm and a simulated annealing algorithm is proposed in this paper. Furthermore, a novel mutation strategy is introduced according to the specialty of Shanghai’s thesis sampling to improve the efficiency of sampling inspection; the acceleration of convergence of the algorithm can also take advantage of this. The new algorithm features the traditional genetic algorithm, and it can obtain the global optimum in the optimization process and provide the fairest sampling plan under the constraint of multiple sampling indexes. The experimental results on the master’s thesis dataset of Shanghai show that the proposed algorithm well meets the requirements of the sampling inspection in Shanghai with a lower time-complexity.
      Citation: Future Internet
      PubDate: 2018-07-30
      DOI: 10.3390/fi10080071
      Issue No: Vol. 10, No. 8 (2018)
  • Future Internet, Vol. 10, Pages 72: Context Analysis of Cloud Computing
           Systems Using a Pattern-Based Approach

    • Authors: Ludger Goeke, Nazila Gol Mohammadi, Maritta Heisel
      First page: 72
      Abstract: Cloud computing services bring new capabilities for hosting and offering complex collaborative business operations. However, these advances might bring undesirable side-effects, e.g., introducing new vulnerabilities and threats caused by collaboration and data exchange over the Internet. Hence, users have become more concerned about security and privacy aspects. For secure provisioning of a cloud computing service, security and privacy issues must be addressed by using a risk assessment method. To perform a risk assessment, it is necessary to obtain all relevant information about the context of the considered cloud computing service. The context analysis of a cloud computing service and its underlying system is a difficult task because of the variety of different types of information that have to be considered. This context information includes (i) legal, regulatory and/or contractual requirements that are relevant for a cloud computing service (indirect stakeholders); (ii) relations to other involved cloud computing services; (iii) high-level cloud system components that support the involved cloud computing services; (iv) data that is processed by the cloud computing services; and (v) stakeholders that interact directly with the cloud computing services and/or the underlying cloud system components. We present a pattern for the contextual analysis of cloud computing services and demonstrate the instantiation of our proposed pattern with real-life application examples. Our pattern contains elements that represent the above-mentioned types of contextual information. The elements of our pattern conform to the General Data Protection Regulation. Besides the context analysis, our pattern supports the identification of high-level assets. Additionally, our proposed pattern supports the documentation of the scope and boundaries of a cloud computing service conforming to the requirements of the ISO 27005 standard (information security risk management). The results of our context analysis contribute to the transparency of the achieved security and privacy level of a cloud computing service. This transparency can increase the trust of users in a cloud computing service. We present results of the RestAssured project related to the context analysis regarding cloud computing services and their underlying cloud computing systems. The context analysis is the prerequisite to threat and control identification that are performed later in the risk management process. The focus of this paper is the use of a pattern at the time of design systematic context analysis and scope definition for risk management methods.
      Citation: Future Internet
      PubDate: 2018-07-31
      DOI: 10.3390/fi10080072
      Issue No: Vol. 10, No. 8 (2018)
  • Future Internet, Vol. 10, Pages 73: Joint AP Association and Bandwidth
           Allocation Optimization Algorithm in High-Dense WLANs

    • Authors: Jianjun Lei, Jiarui Tao, Shanshan Yang
      First page: 73
      Abstract: Regarding access point (AP) overload and performance anomaly which is caused by mobile terminals with different bitrates, a joint AP association and bandwidth allocation optimization algorithm is presented in this paper. Meanwhile, load balancing and proportional fairness are analyzed and formulated as an optimization model. Then, we present a Fair Bandwidth Allocation algorithm based on clients’ Business Priority (FBA-BP), which allocates bandwidth based on the bandwidth demand of clients and their business priority. Furthermore, we propose a Categorized AP Association algorithm based on clients’ demands (CAA-BD), which classifies APs by different types of clients and chooses an optimal associating AP for a new client according to AP categories and the aggregated demand transmission time that are calculated by the FBA-BP algorithm. The CAA-BD can achieve load balance and solve the performance anomaly caused by multi-rate clients coexisting. The simulation results show that our proposed algorithm obtains significant performance in terms of AP utilization, throughput, transmission delay and channel fairness in different client density levels compared with the categorized and Strong Signal First (SSF) algorithms.
      Citation: Future Internet
      PubDate: 2018-08-06
      DOI: 10.3390/fi10080073
      Issue No: Vol. 10, No. 8 (2018)
  • Future Internet, Vol. 10, Pages 74: Predict and Forward: An Efficient
           Routing-Delivery Scheme Based on Node Profile in Opportunistic Networks

    • Authors: Kanghuai Liu, Zhigang Chen, Jia Wu, Yutong Xiao, Heng Zhang
      First page: 74
      Abstract: In the social scene of opportunistic networks, message applications find suitable relay nodes or certain transmission destinations from the surrounding neighbors through specific network addresses of users. However, at the dawn of big data and 5G networks, the variational location information of nodes is difficult to be available to mobile devices all the time, and a long wait for the destination may cause severe end-to-end delay. To improve the transmission environment, this study constructs an efficient routing-delivery scheme (Predict and Forward) based on node profile for the opportunistic networks. The node profile effectively characterizes nodes by analyzing and comparing their attributes instead of network addresses, such as physical characteristics, places of residence, workplaces, occupations or hobbies. According to the optimal stopping theory, this algorithm implements the optimal transmission for Prelearn messages by dividing the complex data transmission process into two different phases (Predict and Forward). Through simulations and the comparison of routing algorithms in opportunistic networks, the proposed strategy increases the delivery ratio by 80% with the traditional methods on average, and the average end-to-end delay in this algorithm is the lowest.
      Citation: Future Internet
      PubDate: 2018-08-06
      DOI: 10.3390/fi10080074
      Issue No: Vol. 10, No. 8 (2018)
  • Future Internet, Vol. 10, Pages 75: A Hierarchical Mapping System for Flat
           Identifier to Locator Resolution Based on Active Degree

    • Authors: Jianqiang Liu, Shuai Huo, Yi Wang
      First page: 75
      Abstract: Overloading of IP address semantics appeals for a new network architecture based on Identifier (ID)/Locator separation. The challenge of Identifier (ID)/Locator separation is how to solve the scalability and efficiency challenges of identity-to-location resolution. By analyzing the requirements of the Identifier (ID)/Locator separation protocol, this paper proposes a hierarchical mapping architecture on active-degree (HMAA). This HMAA was divided into three levels: active local level, neutral transfer level, and inert global level. Each mapping item is dynamically allocated to different levels to ensure minimizing delay according to its activity characteristics. The top layer CHORD is constructed by the Markov Decision Process, which can keep consistency between the physical topology and the logical topology. The simulation results on delay time show that HMAA can satisfy the scalability and efficiency requirements of an Identifier (ID)/Locator separation network.
      Citation: Future Internet
      PubDate: 2018-08-08
      DOI: 10.3390/fi10080075
      Issue No: Vol. 10, No. 8 (2018)
  • Future Internet, Vol. 10, Pages 76: SCADA System Testbed for Cybersecurity
           Research Using Machine Learning Approach

    • Authors: Marcio Andrey Teixeira, Tara Salman, Maede Zolanvari, Raj Jain, Nader Meskin, Mohammed Samaka
      First page: 76
      Abstract: This paper presents the development of a Supervisory Control and Data Acquisition (SCADA) system testbed used for cybersecurity research. The testbed consists of a water storage tank’s control system, which is a stage in the process of water treatment and distribution. Sophisticated cyber-attacks were conducted against the testbed. During the attacks, the network traffic was captured, and features were extracted from the traffic to build a dataset for training and testing different machine learning algorithms. Five traditional machine learning algorithms were trained to detect the attacks: Random Forest, Decision Tree, Logistic Regression, Naïve Bayes and KNN. Then, the trained machine learning models were built and deployed in the network, where new tests were made using online network traffic. The performance obtained during the training and testing of the machine learning models was compared to the performance obtained during the online deployment of these models in the network. The results show the efficiency of the machine learning models in detecting the attacks in real time. The testbed provides a good understanding of the effects and consequences of attacks on real SCADA environments.
      Citation: Future Internet
      PubDate: 2018-08-09
      DOI: 10.3390/fi10080076
      Issue No: Vol. 10, No. 8 (2018)
  • Future Internet, Vol. 10, Pages 77: Motives for Instagram Use and Topics
           of Interest among Young Adults

    • Authors: Yi-Ting Huang, Sheng-Fang Su
      First page: 77
      Abstract: Instagram is currently the most popular social media app among young people around the world. More than 70% of people between the ages of 12 and 24 are Instagram users. The research framework of this study was constructed based on smartphone addiction and the uses and gratifications theory. We used 27 question items divided into five factors, namely social interaction, documentation, diversion, self-promotion, and creativity, to investigate the motives for Instagram use and topics of interest among university students in Taiwan. A total of 307 valid questionnaires were obtained. The results revealed that on the whole, the motives for Instagram use were mostly to look at posts, particularly involving social interaction and diversion motives. The level of agreement expressed toward motives for creating posts was lower. Gender, professional training background, and level of addiction to Instagram all exert influence on motives for Instagram use. Over half of the students majoring in design followed artisans and celebrities (including designers), and female students noticed ads on Instagram more than male students did.
      Citation: Future Internet
      PubDate: 2018-08-09
      DOI: 10.3390/fi10080077
      Issue No: Vol. 10, No. 8 (2018)
  • Future Internet, Vol. 10, Pages 78: Smart Collection of Real-Time
           Vehicular Mobility Traces

    • Authors: Nisrine Ibadah, Khalid Minaoui, Mohammed Rziza, Mohammed Oumsis, César Benavente-Peces
      First page: 78
      Abstract: Mobility trace techniques makes possible drawing the behaviors of real-life movement which shape wireless networks mobility whereabouts. In our investigation, several trace mobility models have been collected after the devices’ deployment. The main issue of this classical procedure is that it produces uncompleted records due to several unpredictable problems occurring during the deployment phase. In this paper, we propose a new procedure aimed at collecting traces while deployment phase failures are avoided, which improves the reliability of data. The introduced procedure makes possible the complete generation of traces with a minimum amount of damage without the need to recover mobile devices or lose them, as it is the case in previous mobility traces techniques. Based on detecting and correcting all accidental issues in real time, the proposed trace scanning offers a set of relevant information about the vehicle status which was collected during seven months. Furthermore, the proposed procedure could be applied to generate vehicular traces. Likewise, it is suitable to record/generate human and animal traces. The research outcomes demonstrate the effectiveness and robustness of the smart collection algorithm based on the proposed trace mobility model.
      Citation: Future Internet
      PubDate: 2018-08-09
      DOI: 10.3390/fi10080078
      Issue No: Vol. 10, No. 8 (2018)
  • Future Internet, Vol. 10, Pages 79: Queue Spillover Management in a
           Connected Vehicle Environment

    • Authors: Chuanxiang Ren, Wenbo Zhang, Lingqiao Qin, Bo Sun
      First page: 79
      Abstract: To alleviate the queue spillovers at intersections of urban roads during rush hours, a solution to the cross-spill problem based on vehicle networking technologies is proposed. This involves using connected vehicle technology, to realize the interactive information on vehicle and intersection signal control. The maximum control distance between intersections is determined by how vehicles are controlled and would travel in that connected environment. A method of calculating overflow tendency towards intersection queuing is also proposed, based on the maximum phase control distance. By this method, the intersection overflow is identified, and then the signal phases are re-optimized according to the requirements of different phases. Finally, overflow prevention control was also performed in this study. The VISSIM simulation results show that the method can better prevent the overflow of queues at intersections.
      Citation: Future Internet
      PubDate: 2018-08-10
      DOI: 10.3390/fi10080079
      Issue No: Vol. 10, No. 8 (2018)
  • Future Internet, Vol. 10, Pages 80: A Fast and Lightweight Method with
           Feature Fusion and Multi-Context for Face Detection

    • Authors: Lei Zhang, Xiaoli Zhi
      First page: 80
      Abstract: Convolutional neural networks (CNN for short) have made great progress in face detection. They mostly take computation intensive networks as the backbone in order to obtain high precision, and they cannot get a good detection speed without the support of high-performance GPUs (Graphics Processing Units). This limits CNN-based face detection algorithms in real applications, especially in some speed dependent ones. To alleviate this problem, we propose a lightweight face detector in this paper, which takes a fast residual network as backbone. Our method can run fast even on cheap and ordinary GPUs. To guarantee its detection precision, multi-scale features and multi-context are fully exploited in efficient ways. Specifically, feature fusion is used to obtain semantic strongly multi-scale features firstly. Then multi-context including both local and global context is added to these multi-scale features without extra computational burden. The local context is added through a depthwise separable convolution based approach, and the global context by a simple global average pooling way. Experimental results show that our method can run at about 110 fps on VGA (Video Graphics Array)-resolution images, while still maintaining competitive precision on WIDER FACE and FDDB (Face Detection Data Set and Benchmark) datasets as compared with its state-of-the-art counterparts.
      Citation: Future Internet
      PubDate: 2018-08-17
      DOI: 10.3390/fi10080080
      Issue No: Vol. 10, No. 8 (2018)
  • Future Internet, Vol. 10, Pages 81: Interactive 3D Exploration of RDF
           Graphs through Semantic Planes

    • Authors: Fabio Viola, Luca Roffia, Francesco Antoniazzi, Alfredo D’Elia, Cristiano Aguzzi, Tullio Salmon Cinotti
      First page: 81
      Abstract: This article presents Tarsier, a tool for the interactive 3D visualization of RDF graphs. Tarsier is mainly intended to support teachers introducing students to Semantic Web data representation formalisms and developers in the debugging of applications based on Semantic Web knowledge bases. The tool proposes the metaphor of semantic planes as a way to visualize an RDF graph. A semantic plane contains all the RDF terms sharing a common concept; it can be created, and further split into several planes, through a set of UI controls or through SPARQL 1.1 queries, with the full support of OWL and RDFS. Thanks to the 3D visualization, links between semantic planes can be highlighted and the user can navigate within the 3D scene to find the better perspective to analyze data. Data can be gathered from generic SPARQL 1.1 protocol services. We believe that Tarsier will enhance the human friendliness of semantic technologies by: (1) helping newcomers assimilate new data representation formats; and (2) increasing the capabilities of inspection to detect relevant situations even in complex RDF graphs.
      Citation: Future Internet
      PubDate: 2018-08-17
      DOI: 10.3390/fi10080081
      Issue No: Vol. 10, No. 8 (2018)
  • Future Internet, Vol. 10, Pages 56: Big Data Perspective and Challenges in
           Next Generation Networks

    • Authors: Kashif Sultan, Hazrat Ali, Zhongshan Zhang
      First page: 56
      Abstract: With the development towards the next generation cellular networks, i.e., 5G, the focus has shifted towards meeting the higher data rate requirements, potential of micro cells and millimeter wave spectrum. The goals for next generation networks are very high data rates, low latency and handling of big data. The achievement of these goals definitely require newer architecture designs, upgraded technologies with possible backward support, better security algorithms and intelligent decision making capability. In this survey, we identify the opportunities which can be provided by 5G networks and discuss the underlying challenges towards implementation and realization of the goals of 5G. This survey also provides a discussion on the recent developments made towards standardization, the architectures which may be potential candidates for deployment and the energy concerns in 5G networks. Finally, the paper presents a big data perspective and the potential of machine learning for optimization and decision making in 5G networks.
      Citation: Future Internet
      PubDate: 2018-06-21
      DOI: 10.3390/fi10070056
      Issue No: Vol. 10, No. 7 (2018)
  • Future Internet, Vol. 10, Pages 57: Dynamic Cost-Aware Routing of Web

    • Authors: Gandhimathi Velusamy, Ricardo Lent
      First page: 57
      Abstract: Work within next generation networks considers additional network convergence possibilities and the integration of new services to the web. This trend responds to the ongoing growth of end-user demand for services that can be delivered anytime, anywhere, on any web-capable device, and of traffic generated by new applications, e.g., the Internet of Things. To support the massive traffic generated by the enormous user base and number of devices with reliability and high quality, web services run from redundant servers. As new servers need to be regularly deployed at different geographical locations, energy costs have become a source of major concern for operators. We propose a cost aware method for routing web requests across replicated and distributed servers that can exploit the spatial and temporal variations of both electricity prices and the server network. The method relies on a learning automaton that makes per-request decisions, which can be computed much faster than regular global optimization methods. Using simulation and testbed measurements, we show the cost reductions that are achievable with minimal impact on performance compared to standard web routing algorithms.
      Citation: Future Internet
      PubDate: 2018-06-21
      DOI: 10.3390/fi10070057
      Issue No: Vol. 10, No. 7 (2018)
  • Future Internet, Vol. 10, Pages 58: Fuzzy Multi-Criteria Based Trust
           Management in Heterogeneous Federated Future Internet Testbeds

    • Authors: Dimitrios Dechouniotis, Ioannis Dimolitsas, Konstantinos Papadakis-Vlachopapadopoulos, Symeon Papavassiliou
      First page: 58
      Abstract: A federation of heterogeneous testbeds, which provides a wide range of services, attracts many experimenters from academia and industry to evaluate novel future Internet architectures and network protocols. The candidate experimenter reserves the appropriate testbeds’ resources based on various diverse criteria. Since several testbeds offer similar resources, a trust mechanism between the users and the providers will facilitate the proper selection of testbeds. This paper proposes a fuzzy reputation-based trust framework that is based on a modification of the fuzzy VIKOR multi-criteria decision making method and combines the user’s opinion from previously-conducted experiments with retrieved monitoring data from the utilized testbeds, in order to quantify the reputation of each testbed and the credibility of the experimenter. The proposed framework can process various types of numeric and linguistic data in an on-line fashion and can be easily extended for new types of testbeds and services. Data from active federated testbeds are used to evaluate the performance of the fuzzy reputation-based trust framework under dynamic conditions. Furthermore, a comparison of the proposed framework with another existing state of the art trust framework for federated testbeds is presented, and its superiority is demonstrated.
      Citation: Future Internet
      PubDate: 2018-06-25
      DOI: 10.3390/fi10070058
      Issue No: Vol. 10, No. 7 (2018)
  • Future Internet, Vol. 10, Pages 59: Clock Recovery Challenges in DSP-Based
           Coherent Single-Mode and Multi-Mode Optical Systems

    • Authors: Júlio César Medeiros Diniz, Francesco Da Ros, Darko Zibar
      First page: 59
      Abstract: We present an analysis of clock recovery algorithms in both polarization division multiplexing systems and mode division multiplexing systems. The impact of inter-polarization time skew and polarization mode dispersion in single-mode fibers, as well as the combined impact of mode mixing and mode group delay spread in multi-mode fibers under different coupling regimes are investigated. Results show that although the clock tone vanishing has a known solution for single-mode systems, in multi-mode systems even for low group delay spread, strong coupling will cause clock tone extinction, making it harder to implement an effective clock recovery scheme.
      Citation: Future Internet
      PubDate: 2018-06-26
      DOI: 10.3390/fi10070059
      Issue No: Vol. 10, No. 7 (2018)
  • Future Internet, Vol. 10, Pages 60: A Novel Two-Layered Reinforcement
           Learning for Task Offloading with Tradeoff between Physical Machine
           Utilization Rate and Delay

    • Authors: Li Quan, Zhiliang Wang, Fuji Ren
      First page: 60
      Abstract: Mobile devices could augment their ability via cloud resources in mobile cloud computing environments. This paper developed a novel two-layered reinforcement learning (TLRL) algorithm to consider task offloading for resource-constrained mobile devices. As opposed to existing literature, the utilization rate of the physical machine and the delay for offloaded tasks are taken into account simultaneously by introducing a weighted reward. The high dimensionality of the state space and action space might affect the speed of convergence. Therefore, a novel reinforcement learning algorithm with a two-layered structure is presented to address this problem. First, k clusters of the physical machines are generated based on the k-nearest neighbors algorithm (k-NN). The first layer of TLRL is implemented by a deep reinforcement learning to determine the cluster to be assigned for the offloaded tasks. On this basis, the second layer intends to further specify a physical machine for task execution. Finally, simulation examples are carried out to verify that the proposed TLRL algorithm is able to speed up the optimal policy learning and can deal with the tradeoff between physical machine utilization rate and delay.
      Citation: Future Internet
      PubDate: 2018-07-01
      DOI: 10.3390/fi10070060
      Issue No: Vol. 10, No. 7 (2018)
  • Future Internet, Vol. 10, Pages 61: Personalised and Coordinated
           Demand-Responsive Feeder Transit Service Design: A Genetic Algorithms

    • Authors: Bo Sun, Ming Wei, Chunfeng Yang, Zhihuo Xu, Han Wang
      First page: 61
      Abstract: The purpose of this work is to create an efficient optimization framework for demand-responsive feeder transit services to assign vehicles to cover all pickup locations to transport passengers to a rail station. The proposed methodology features passengers placing a personalized travel order involving the subway schedule chosen by passengers and windows of service time, etc. Moreover, synchronous transfer between the shuttle and feeder bus is fully accounted for in the problem. A mixed-integer linear programming model is formulated to minimize the total travel time for all passengers, which consists of ride-time for vehicles from the pickup locations to the rail station and wait-time for passengers taking the subway beforehand. Different from conventional methods, the proposed model benefits from using a real distribution of passenger demand aggregated from cellular data and travel time or the distance matrix obtained from an open GIS tool. A distributed genetic algorithm is further designed to obtain meta-optimal solutions in a reasonable amount of time. When applied to design a feeder bus system in Nanjing City, China, case study results reveal that the total travel time of the proposed model was reduced by 2.46% compared to the traditional model. Sensitivity analyses were also further performed to investigate the impact of the number of vehicles on the output. Finally, the difference in results of Cplex, standard GA, and the proposed algorithm were compared to prove the validity of the algorithm.
      Citation: Future Internet
      PubDate: 2018-07-01
      DOI: 10.3390/fi10070061
      Issue No: Vol. 10, No. 7 (2018)
  • Future Internet, Vol. 10, Pages 62: The GDPR beyond Privacy: Data-Driven
           Challenges for Social Scientists, Legislators and Policy-Makers

    • Authors: Margherita Vestoso
      First page: 62
      Abstract: While securing personal data from privacy violations, the new General Data Protection Regulation (GDPR) explicitly challenges policymakers to exploit evidence from social data-mining in order to build better policies. Against this backdrop, two issues become relevant: the impact of Big Data on social research, and the potential intersection between social data mining, rulemaking and policy modelling. The work aims at contributing to the reflection on some of the implications of the ‘knowledge-based’ policy recommended by the GDPR. The paper is thus split into two parts: the first describes the data-driven evolution of social sciences, raising methodological and epistemological issues; the second focuses on the interplay between data-driven social research, rule-making and policy modelling, in the light of the policy model fostered by GDPR. Some theoretical reflections about the role of evidence in rule-making will be considered to introduce a discussion on the intersection between data-driven social research and policy modelling and to sketch hypotheses on its future evolutions.
      Citation: Future Internet
      PubDate: 2018-07-06
      DOI: 10.3390/fi10070062
      Issue No: Vol. 10, No. 7 (2018)
  • Future Internet, Vol. 10, Pages 63: Towards Prediction of Immersive
           Virtual Reality Image Quality of Experience and Quality of Service

    • Authors: Anil Kumar Karembai, Jeffrey Thompson, Patrick Seeling
      First page: 63
      Abstract: In this article, we evaluate the Quality of Service (QoS) through media impairment levels and device operators’ subjective Quality of Experience (QoE). The human-centered QoE determination commonly requires human subject experimentation, which we combine with Electroencephalography (EEG) measurements to move towards automatized and generalized possibilities of determining the QoE. We evaluate the prediction performance for spherical/immersive images displayed with a mobile device VR viewer (Spherical Virtual Reality (SVR)) with the help of only four-position EEG data gathered at the forehead, which correlates well with practical applicability. We find that QoS levels can be predicted more reliably (directly with R2=0.68 or based on profiles with R2=0.9) than the QoE, which exhibits significant error levels. Additional comparison with previous approaches for the Spherical Augmented Reality (SAR) QoE indicates better predictability in AR scenarios over VR.
      Citation: Future Internet
      PubDate: 2018-07-07
      DOI: 10.3390/fi10070063
      Issue No: Vol. 10, No. 7 (2018)
  • Future Internet, Vol. 10, Pages 64: Dynamic Traffic Scheduling and
           Congestion Control across Data Centers Based on SDN

    • Authors: Dong Sun, Kaixin Zhao, Yaming Fang, Jie Cui
      First page: 64
      Abstract: Software-defined Networking (SDN) and Data Center Network (DCN) are receiving considerable attention and eliciting widespread interest from both academia and industry. When the traditionally shortest path routing protocol among multiple data centers is used, congestion will frequently occur in the shortest path link, which may severely reduce the quality of network services due to long delay and low throughput. The flexibility and agility of SDN can effectively ameliorate the aforementioned problem. However, the utilization of link resources across data centers is still insufficient, and has not yet been well addressed. In this paper, we focused on this issue and proposed an intelligent approach of real-time processing and dynamic scheduling that could make full use of the network resources. The traffic among the data centers could be classified into different types, and different strategies were proposed for these types of real-time traffic. Considering the prolonged occupation of the bandwidth by malicious flows, we employed the multilevel feedback queue mechanism and proposed an effective congestion control algorithm. Simulation experiments showed that our scheme exhibited the favorable feasibility and demonstrated a better traffic scheduling effect and great improvement in bandwidth utilization across data centers.
      Citation: Future Internet
      PubDate: 2018-07-09
      DOI: 10.3390/fi10070064
      Issue No: Vol. 10, No. 7 (2018)
  • Future Internet, Vol. 10, Pages 65: Performance Analysis of Hybrid
           Optical–Acoustic AUV Swarms for Marine Monitoring

    • Authors: Chiara Lodovisi, Pierpaolo Loreti, Lorenzo Bracciale, Silvello Betti
      First page: 65
      Abstract: Autonomous Underwater Vehicles (AUVs) are assuming an important role in the monitoring and mapping of marine ecosystems, especially for their ability to explore harsh environments. AUV swarm can collect data operating autonomously for long periods enabling new applications in this field. However, the mission duration is usually limited also by the high power consumption required for acoustic transmissions. A new generation of devices complements the acoustic modem with an optical modem that can provide a communication channel with higher capacity and lower power consumption with respect to the acoustic channel. However, the optical link that uses the visible light is very sensitive to the water turbidity that can strongly limit the link coverage. In this paper, we evaluate the networking performances of the Venus vessel, a real AUV prototype equipped with an acoustical modem and an optical modem. The presented analysis aims to evaluate key system parameters allowing to select the best way to set up network communications according to the surrounding conditions (e.g., quality of water) and to the application requirements. Simulation results account for the case of ports or basins, where the water quality is poor and the use of the optical modem is strongly limited by distance. We evaluate system performance in terms of transmission delay in the network and we also provide a power–capacity trade-off.
      Citation: Future Internet
      PubDate: 2018-07-10
      DOI: 10.3390/fi10070065
      Issue No: Vol. 10, No. 7 (2018)
  • Future Internet, Vol. 10, Pages 66: Enabling Trustworthy Multicast
           Wireless Services through D2D Communications in 5G Networks

    • Authors: Sara Pizzi, Chiara Suraci, Leonardo Militano, Antonino Orsino, Antonella Molinaro, Antonio Iera, Giuseppe Araniti
      First page: 66
      Abstract: Device-to-device (D2D) communication is considered as one of the key enabling technologies for fifth-generation (5G) networks as it allows data offloading generated by the huge number of connected devices. In this respect, group-oriented services are among the most interesting usage scenarios. Indeed, D2D can improve the performance of the conventional multicast scheme (CMS) in cellular networks, which is known to suffer from low spectral efficiency. Security is a further key field of investigation for 5G systems, as any threat to privacy and security may lead to both deteriorated user experience and inefficient network resources’ utilization. Security issues are even more in focus for D2D connections between devices that are in mutual proximity. To improve the CMS performance and also sustain security requirements of the 5G network, this work proposes a secure D2D data transmission algorithm. Making use of mechanisms such as encryption and signature, this algorithm aims to protect the exchanged data and the privacy of the devices involved in the communication. A simulation campaign conducted using MATLAB shows the ability of the proposed solution to take advantage of the establishment of secure D2D communications and efficiently utilize network resources.
      Citation: Future Internet
      PubDate: 2018-07-11
      DOI: 10.3390/fi10070066
      Issue No: Vol. 10, No. 7 (2018)
  • Future Internet, Vol. 10, Pages 67: Network Measurement and Performance
           Analysis at Server Side

    • Authors: Guang-Qian Peng, Guangtao Xue, Yi-Chao Chen
      First page: 67
      Abstract: Network performance diagnostics is an important topic that has been studied since the Internet was invented. However, it remains a challenging task, while the network evolves and becomes more and more complicated over time. One of the main challenges is that all network components (e.g., senders, receivers, and relay nodes) make decision based only on local information and they are all likely to be performance bottlenecks. Although Software Defined Networking (SDN) proposes to embrace a centralize network intelligence for a better control, the cost to collect complete network states in packet level is not affordable in terms of collection latency, bandwidth, and processing power. With the emergence of the new types of networks (e.g., Internet of Everything, Mission-Critical Control, data-intensive mobile apps, etc.), the network demands are getting more diverse. It is critical to provide finer granularity and real-time diagnostics to serve various demands. In this paper, we present EVA, a network performance analysis tool that guides developers and network operators to fix problems in a timely manner. EVA passively collects packet traces near the server (hypervisor, NIC, or top-of-rack switch), and pinpoints the location of the performance bottleneck (sender, network, or receiver). EVA works without detailed knowledge of application or network stack and is therefore easy to deploy. We use three types of real-world network datasets and perform trace-driven experiments to demonstrate EVA’s accuracy and generality. We also present the problems observed in these datasets by applying EVA.
      Citation: Future Internet
      PubDate: 2018-07-16
      DOI: 10.3390/fi10070067
      Issue No: Vol. 10, No. 7 (2018)
  • Future Internet, Vol. 10, Pages 46: A Tiered Control Plane Model for
           Service Function Chaining Isolation

    • Authors: Håkon Gunleifsen, Vasileios Gkioulos, Thomas Kemmerich
      First page: 46
      Abstract: This article presents an architecture for encryption automation in interconnected Network Function Virtualization (NFV) domains. Current NFV implementations are designed for deployment within trusted domains, where overlay networks with static trusted links are utilized for enabling network security. Nevertheless, within a Service Function Chain (SFC), Virtual Network Function (VNF) flows cannot be isolated and end-to-end encrypted because each VNF requires direct access to the overall SFC data-flow. This restricts both end-users and Service Providers from enabling end-to-end security, and in extended VNF isolation within the SFC data traffic. Encrypting data flows on a per-flow basis results in an extensive amount of secure tunnels, which cannot scale efficiently in manual configurations. Additionally, creating secure data plane tunnels between NFV providers requires secure exchange of key parameters, and the establishment of an east–west control plane protocol. In this article, we present an architecture focusing on these two problems, investigating how overlay networks can be created, isolated, and secured dynamically. Accordingly, we propose an architecture for automated establishment of encrypted tunnels in NFV, which introduces a novel, tiered east–west communication channel between network controllers in a multi-domain environment.
      Citation: Future Internet
      PubDate: 2018-06-04
      DOI: 10.3390/fi10060046
      Issue No: Vol. 10, No. 6 (2018)
  • Future Internet, Vol. 10, Pages 47: Secure Inter-Frame Space
           Communications for Wireless LANs

    • Authors: Il-Gu Lee
      First page: 47
      Abstract: The internet of things (IoTs) offers a wide range of consumer benefits, from personal portable devices to internet-connected infrastructure. The wireless local area network (WLAN) is one of the potential candidates for IoTs technology to connect billions of smart devices. Long-range WLAN is widely deployed in dense networks as an alternative to cellular networks or satellite internet access because of its low cost, high performance, and existing ecosystem. However, due to the nature of unregulated communications in industrial, scientific, and medical (ISM) bands, WLANs experience interferences from other radios such as radars and frequency hopping devices. Once interference is detected at a WLAN device, the channel is avoided and other channels become crowded. Thus, it degrades network throughput and channel utilization. In this paper, a secure inter-frame space communication system design is proposed for WLANs to share the ISM bands with other radio systems that generate periodic radio signals. The proposed secure inter-frame communication scheme achieves the goal by designing accurate radar detection and secure inter-frame space communication. The simulation results demonstrate that the proposed scheme significantly increases the receiver sensitivity and user datagram protocol throughput.
      Citation: Future Internet
      PubDate: 2018-06-04
      DOI: 10.3390/fi10060047
      Issue No: Vol. 10, No. 6 (2018)
  • Future Internet, Vol. 10, Pages 48: On the Future of Legal Publishing
           Services in the Semantic Web

    • Authors: Enrico Francesconi
      First page: 48
      Abstract: The development of the Semantic Web represents an essential precondition to the definition of new scenarios for the future Internet. This perspective is of particular interest in the legal information domain for the specialized nature of legal information and the peculiarities of the legal users’ information needs. In this paper, the evolution in recent years of the Semantic Web in the legal domain is reviewed, with particular emphasis to the most recent developments related to Linked Open Data initiative and to the role, in the legal Semantic Web, of the Publications Office of the European Union in its two-fold role of public institution and legal publisher.
      Citation: Future Internet
      PubDate: 2018-06-05
      DOI: 10.3390/fi10060048
      Issue No: Vol. 10, No. 6 (2018)
  • Future Internet, Vol. 10, Pages 49: Certificateless Provable Group Shared

    • Authors: Hongbin Yang, Shuxiong Jiang, Wenfeng Shen, Zhou Lei
      First page: 49
      Abstract: Provable Data Possession (PDP) protocol makes it possible for cloud users to check whether the cloud servers possess their original data without downloading all the data. However, most of the existing PDP schemes are based on either public key infrastructure (PKI) or identity-based cryptography, which will suffer from issues of expensive certificate management or key escrow. In this paper, we propose a new construction of certificateless provable group shared data possession (CL-PGSDP) protocol by making use of certificateless cryptography, which will eliminate the above issues. Meanwhile, by taking advantage of zero-knowledge protocol and randomization method, the proposed CL-PGSDP protocol leaks no information of the stored data and the group user’s identity to the verifiers during the verifying process, which is of the property of comprehensive privacy preservation. In addition, our protocol also supports efficient user revocation from the group. Security analysis and experimental evaluation indicate that our CL-PGSDP protocol provides strong security with desirable efficiency.
      Citation: Future Internet
      PubDate: 2018-06-07
      DOI: 10.3390/fi10060049
      Issue No: Vol. 10, No. 6 (2018)
  • Future Internet, Vol. 10, Pages 50: Fairness and Trust in Virtual
           Environments: The Effects of Reputation

    • Authors: Mirko Duradoni, Mario Paolucci, Franco Bagnoli, Andrea Guazzini
      First page: 50
      Abstract: Reputation supports pro-social behaviors in a variety of social settings and across different ages. When re-encounters are possible, developing a positive reputation can be a valuable asset that will result in better outcomes. However, in real life, cooperative acts are ambiguous and happen in noisy environments in which individuals can have multiple goals, visibility is reduced, and reputation systems may differ. This study examined how reputation within a virtual environment affects fairness in material allocations and trust in information exchange, in a three-actors interaction game in which each player had an incentive to deceive the others. We compared the results of two experimental conditions, one in which informers could be evaluated, and one without reputational opportunities. A reputational system appeared to enhance both trust and fairness even within a virtual environment under anonymous condition. We tested adolescents and adults finding that they were consistently more generous when visibility was increased, but they showed significantly different patterns in resources allocation and information exchange. Male and female participants, across ages, showed other interesting differences. These findings suggest that reputational effects increase fairness and trust even in a noisy, ambiguous and uncertain environment, but this effect is modulated by age and gender.
      Citation: Future Internet
      PubDate: 2018-06-09
      DOI: 10.3390/fi10060050
      Issue No: Vol. 10, No. 6 (2018)
  • Future Internet, Vol. 10, Pages 51: A Driving Behavior Planning and
           Trajectory Generation Method for Autonomous Electric Bus

    • Authors: Lingli Yu, Decheng Kong, Xiaoxin Yan
      First page: 51
      Abstract: A framework of path planning for autonomous electric bus is presented. ArcGIS platform is utilized for map-building and global path planning. Firstly, a high-precision map is built based on GPS in ArcGIS for global planning. Then the global optimal path is obtained by network analysis tool in ArcGIS. To facilitate local planning, WGS-84 coordinates in the map are converted to local coordinates. Secondly, a double-layer finite state machine (FSM) is devised to plan driving behavior under different driving scenarios, such as structured driving, lane changing, turning, and so on. Besides, local optimal trajectory is generated by cubic polynomial, which takes full account of the safety and kinetics of the electric bus. Finally, the simulation results show that the framework is reliable and feasible for driving behavior planning and trajectory generation. Furthermore, its validity is proven with an autonomous bus platform 12 m in length.
      Citation: Future Internet
      PubDate: 2018-06-10
      DOI: 10.3390/fi10060051
      Issue No: Vol. 10, No. 6 (2018)
  • Future Internet, Vol. 10, Pages 52: A Novel Self-Adaptive VM Consolidation
           Strategy Using Dynamic Multi-Thresholds in IaaS Clouds

    • Authors: Lei Xie, Shengbo Chen, Wenfeng Shen, Huaikou Miao
      First page: 52
      Abstract: With the rapid development of cloud computing, the demand for infrastructure resources in cloud data centers has further increased, which has already led to enormous amounts of energy costs. Virtual machine (VM) consolidation as one of the important techniques in Infrastructure as a Service clouds (IaaS) can help resolve energy consumption by reducing the number of active physical machines (PMs). However, the necessity of considering energy-efficiency and the obligation of providing high quality of service (QoS) to customers is a trade-off, as aggressive consolidation may lead to performance degradation. Moreover, most of the existing works of threshold-based VM consolidation strategy are mainly focused on single CPU utilization, although the resource request on different VMs are very diverse. This paper proposes a novel self-adaptive VM consolidation strategy based on dynamic multi-thresholds (DMT) for PM selection, which can be dynamically adjusted by considering future utilization on multi-dimensional resources of CPU, RAM and Bandwidth. Besides, the VM selection and placement algorithm of VM consolidation are also improved by utilizing each multi-dimensional parameter in DMT. The experiments show that our proposed strategy has a better performance than other strategies, not only in high QoS but also in less energy consumption. In addition, the advantage of its reduction on the number of active hosts is much more obvious, especially when it is under extreme workloads.
      Citation: Future Internet
      PubDate: 2018-06-13
      DOI: 10.3390/fi10060052
      Issue No: Vol. 10, No. 6 (2018)
  • Future Internet, Vol. 10, Pages 53: A Privacy Preserving Framework for
           Worker’s Location in Spatial Crowdsourcing Based on Local Differential

    • Authors: Jiazhu Dai, Keke Qiao
      First page: 53
      Abstract: With the development of the mobile Internet, location-based services are playing an important role in everyday life. As a new location-based service, Spatial Crowdsourcing (SC) involves collecting and analyzing environmental, social, and other spatiotemporal information of individuals, increasing convenience for users. In SC, users (called requesters) publish tasks and other users (called workers) are required to physically travel to specified locations to perform the tasks. However, with SC services, the workers have to disclose their locations to untrusted third parties, such as the Spatial Crowdsourcing Server (SC-server), which could pose a considerable threat to the privacy of workers. In this paper, we propose a new location privacy protection framework based on local difference privacy for spatial crowdsourcing, which does not require the participation of trusted third parties by adding noises locally to workers’ locations. The noisy locations of workers are submitted to the SC-server rather than the real locations. Therefore, the protection of workers’ locations is achieved. Experiments showed that this framework not only preserves the privacy of workers in SC, but also has modest overhead performance.
      Citation: Future Internet
      PubDate: 2018-06-14
      DOI: 10.3390/fi10060053
      Issue No: Vol. 10, No. 6 (2018)
  • Future Internet, Vol. 10, Pages 54: StegNet: Mega Image Steganography
           Capacity with Deep Convolutional Network

    • Authors: Pin Wu, Yang Yang, Xiaoqiang Li
      First page: 54
      Abstract: Traditional image steganography often leans interests towards safely embedding hidden information into cover images with payload capacity almost neglected. This paper combines recent deep convolutional neural network methods with image-into-image steganography. It successfully hides the same size images with a decoding rate of 98.2% or bpp (bits per pixel) of 23.57 by changing only 0.76% of the cover image on average. Our method directly learns end-to-end mappings between the cover image and the embedded image and between the hidden image and the decoded image. We further show that our embedded image, while with mega payload capacity, is still robust to statistical analysis.
      Citation: Future Internet
      PubDate: 2018-06-15
      DOI: 10.3390/fi10060054
      Issue No: Vol. 10, No. 6 (2018)
  • Future Internet, Vol. 10, Pages 55: Simulating the Cost of Cooperation: A
           Recipe for Collaborative Problem-Solving

    • Authors: Andrea Guazzini, Mirko Duradoni, Alessandro Lazzeri, Giorgio Gronchi
      First page: 55
      Abstract: Collective problem-solving and decision-making, along with other forms of collaboration online, are central phenomena within ICT. There had been several attempts to create a system able to go beyond the passive accumulation of data. However, those systems often neglect important variables such as group size, the difficulty of the tasks, the tendency to cooperate, and the presence of selfish individuals (free riders). Given the complex relations among those variables, numerical simulations could be the ideal tool to explore such relationships. We take into account the cost of cooperation in collaborative problem solving by employing several simulated scenarios. The role of two parameters was explored: the capacity, the group’s capability to solve increasingly challenging tasks coupled with the collective knowledge of a group, and the payoff, an individual’s own benefit in terms of new knowledge acquired. The final cooperation rate is only affected by the cost of cooperation in the case of simple tasks and small communities. In contrast, the fitness of the community, the difficulty of the task, and the groups sizes interact in a non-trivial way, hence shedding some light on how to improve crowdsourcing when the cost of cooperation is high.
      Citation: Future Internet
      PubDate: 2018-06-19
      DOI: 10.3390/fi10060055
      Issue No: Vol. 10, No. 6 (2018)
  • Future Internet, Vol. 10, Pages 114: Privacy and Security Issues in Online
           Social Networks

    • Authors: Shaukat Ali, Naveed Islam, Azhar Rauf, Ikram Ud Din, Mohsen Guizani, Joel J. P. C. Rodrigues
      First page: 114
      Abstract: The advent of online social networks (OSN) has transformed a common passive reader into a content contributor. It has allowed users to share information and exchange opinions, and also express themselves in online virtual communities to interact with other users of similar interests. However, OSN have turned the social sphere of users into the commercial sphere. This should create a privacy and security issue for OSN users. OSN service providers collect the private and sensitive data of their customers that can be misused by data collectors, third parties, or by unauthorized users. In this paper, common security and privacy issues are explained along with recommendations to OSN users to protect themselves from these issues whenever they use social media.
      Citation: Future Internet
      PubDate: 2018-11-22
      DOI: 10.3390/fi10120114
      Issue No: Vol. 10, No. 12 (2018)
  • Future Internet, Vol. 10, Pages 115: Video-Based Human Action Recognition
           Using Spatial Pyramid Pooling and 3D Densely Convolutional Networks

    • Authors: Wanli Yang, Yimin Chen, Chen Huang, Mingke Gao
      First page: 115
      Abstract: In recent years, the application of deep neural networks to human behavior recognition has become a hot topic. Although remarkable achievements have been made in the field of image recognition, there are still many problems to be solved in the area of video. It is well known that convolutional neural networks require a fixed size image input, which not only limits the network structure but also affects the recognition accuracy. Although this problem has been solved in the field of images, it has not yet been broken through in the field of video. To address the input problem of fixed size video frames in video recognition, we propose a three-dimensional (3D) densely connected convolutional network based on spatial pyramid pooling (3D-DenseNet-SPP). As the name implies, the network structure is mainly composed of three parts: 3DCNN, DenseNet, and SPPNet. Our models were evaluated on a KTH dataset and UCF101 dataset separately. The experimental results showed that our model has better performance in the field of video-based behavior recognition in comparison to the existing models.
      Citation: Future Internet
      PubDate: 2018-11-22
      DOI: 10.3390/fi10120115
      Issue No: Vol. 10, No. 12 (2018)
  • Future Internet, Vol. 10, Pages 116: A Bi-Directional LSTM-CNN Model with
           Attention for Aspect-Level Text Classification

    • Authors: Yonghua Zhu, Xun Gao, Weilin Zhang, Shenkai Liu, Yuanyuan Zhang
      First page: 116
      Abstract: The prevalence that people share their opinions on the products and services in their daily lives on the Internet has generated a large quantity of comment data, which contain great business value. As for comment sentences, they often contain several comment aspects and the sentiment on these aspects are different, which makes it meaningless to give an overall sentiment polarity of the sentence. In this paper, we introduce Attention-based Aspect-level Recurrent Convolutional Neural Network (AARCNN) to analyze the remarks at aspect-level. The model integrates attention mechanism and target information analysis, which enables the model to concentrate on the important parts of the sentence and to make full use of the target information. The model uses bidirectional LSTM (Bi-LSTM) to build the memory of the sentence, and then CNN is applied to extracting attention from memory to get the attentive sentence representation. The model uses aspect embedding to analyze the target information of the representation and finally the model outputs the sentiment polarity through a softmax layer. The model was tested on multi-language datasets, and demonstrated that it has better performance than conventional deep learning methods.
      Citation: Future Internet
      PubDate: 2018-11-24
      DOI: 10.3390/fi10120116
      Issue No: Vol. 10, No. 12 (2018)
  • Future Internet, Vol. 10, Pages 117: A Personalized Recommendation
           Algorithm Based on the User’s Implicit Feedback in E-Commerce

    • Authors: Bo Wang, Feiyue Ye, Jialu Xu
      First page: 117
      Abstract: A recommendation system can recommend items of interest to users. However, due to the scarcity of user rating data and the similarity of single ratings, the accuracy of traditional collaborative filtering algorithms (CF) is limited. Compared with user rating data, the user’s behavior log is easier to obtain and contains a large amount of implicit feedback information, such as the purchase behavior, comparison behavior, and sequences of items (item-sequences). In this paper, we proposed a personalized recommendation algorithm based on a user’s implicit feedback (BUIF). BUIF considers not only the user’s purchase behavior but also the user’s comparison behavior and item-sequences. We extracted the purchase behavior, comparison behavior, and item-sequences from the user’s behavior log; calculated the user’s similarity by purchase behavior and comparison behavior; and extended word-embedding to item-embedding to obtain the item’s similarity. Based on the above method, we built a secondary reordering model to generate the recommendation results for users. The results of the experiment on the JData dataset show that our algorithm shows better improvement in regard to recommendation accuracy over other CF algorithms.
      Citation: Future Internet
      PubDate: 2018-11-29
      DOI: 10.3390/fi10120117
      Issue No: Vol. 10, No. 12 (2018)
  • Future Internet, Vol. 10, Pages 118: DSP-Based 40 GB/s Lane Rate
           Next-Generation Access Networks

    • Authors: Jinlong Wei, Ji Zhou, Elias Giacoumidis, Paul A. Haigh, Jianming Tang
      First page: 118
      Abstract: To address the continuous growth in high-speed ubiquitous access required by residential users and enterprises, Telecommunication operators must upgrade their networks to higher data rates. For optical fiber access networks that directly connect end users to metro/regional network, capacity upgrade must be done in a cost- and energy-efficient manner. 40 Gb/s is the possible lane rate for the next generation passive optical networks (NG-PONs). Ideally, existing 10 G PON components could be reused to support 40 Gb/s lane-rate NG-PON transceiver, which requires efficient modulation format and digital signal processing (DSP) to alleviate the bandwidth limitation and fiber dispersion. The major contribution of this work is to offer insight performance comparisons of 40 Gb/s lane rate electrical three level Duobinary, optical Duobinary, and four-level pulse amplitude modulation (PAM-4) for incorporating low complex DSPs, including linear and nonlinear Volterra equalization, as well as maximum likelihood sequence estimation. Detailed analysis and comparison of the complexity of various DSP algorithms are performed. Transceiver bandwidth optimization is also undertaken. The results show that the choices of proper modulation format and DSP configuration depend on the transmission distances of interest.
      Citation: Future Internet
      PubDate: 2018-11-30
      DOI: 10.3390/fi10120118
      Issue No: Vol. 10, No. 12 (2018)
  • Future Internet, Vol. 10, Pages 119: Secure and Dynamic Memory Management
           Architecture for Virtualization Technologies in IoT Devices

    • Authors: Jithin R, Priya Chandran
      First page: 119
      Abstract: The introduction of the internet in embedded devices led to a new era of technology—the Internet of Things (IoT) era. The IoT technology-enabled device market is growing faster by the day, due to its complete acceptance in diverse areas such as domicile systems, the automobile industry, and beyond. The introduction of internet connectivity in objects that are frequently used in daily life raises the question of security—how secure is the information and the infrastructure handled by these devices when they are connected to the internet' Security enhancements through standard cryptographic techniques are not suitable due to the power and performance constraints of IoT devices. The introduction of virtualization technology into IoT devices is a recent development, meant for fulfilling security and performance needs. However, virtualization augments the vulnerability present in IoT devices, due to the addition of one more software layer—namely, the hypervisor, which enables the sharing of resources among different users. This article proposes the adaptation of ASMI (Architectural Support for Memory Isolation—a general architecture available in the literature for the improvement of the performance and security of virtualization technology) on the popular MIPS (Microprocessor without Interlocked Pipeline Stages) embedded virtualization platform, which could be adopted in embedded virtualization architectures for IoT devices. The article illustrates the performance enhancement achieved by the proposed architecture with the existing architectures.
      Citation: Future Internet
      PubDate: 2018-11-30
      DOI: 10.3390/fi10120119
      Issue No: Vol. 10, No. 12 (2018)
  • Future Internet, Vol. 10, Pages 120: Personality and Reputation: A Complex
           Relationship in Virtual Environments

    • Authors: Stefania Collodi, Sara Panerati, Enrico Imbimbo, Federica Stefanelli, Mirko Duradoni, Andrea Guazzini
      First page: 120
      Abstract: Online reputational systems are nowadays widely and effectively adopted by several online platforms to support and improve peoples’ interactions and communication. Despite the research approached and modeled social dynamics of reputational systems in different domains, adopting different frameworks, the role played by psycho-social factors, and personality traits, determining the individual susceptibility to online reputation is still elusive. To study such mediation effects, we implemented a modified online version of the Ultimatum Game, in which participants (215 adolescents) played before as proposers, and then as responders, always knowing the reputation of their interactors. Furthermore, after the reception phase, participants could evaluate the received offers, giving positive or negative feedback to their proposers. Despite the participants’ belief they were playing with their schoolmates, the interactors’ role was always fulfilled by bots characterized by standardized behaviors. Our results show how psychological traits influence the participants’ behavior in all the game phases, as well as in the rating dynamics. Reputation seems to have a direct effect only in the allocation behavior, while, in regards the other dynamics of the game (i.e., acceptance and rating), it comes into play in a complex interaction with the psychological dimensions.
      Citation: Future Internet
      PubDate: 2018-12-01
      DOI: 10.3390/fi10120120
      Issue No: Vol. 10, No. 12 (2018)
  • Future Internet, Vol. 10, Pages 121: Exploiting JTAG and Its Mitigation in
           IOT: A Survey

    • Authors: Gopal Vishwakarma, Wonjun Lee
      First page: 121
      Abstract: Nowadays, companies are heavily investing in the development of “Internet of Things(IoT)” products. These companies usually and obviously hunt for lucrative business models. Currently, each person owns at least 3–4 devices (such as mobiles, personal computers, Google Assistant, Alexa, etc.) that are connected to the Internet 24/7. However, in the future, there might be hundreds of devices that will be constantly online behind each person, keeping track of body health, banking transactions, status of personal devices, etc. to make one’s life more efficient and streamlined. Thus, it is very crucial that each device should be highly secure since one’s life will become dependent on these devices. However, the current security of IoT devices is mainly focused on resiliency of device. In addition, less complex node devices are easily accessible to the public resulting in higher vulnerability. JTAG is an IEEE standard that has been defined to test proper mounting of components on PCBs (printed circuit boards) and has been extensively used by PCB manufacturers to date. This JTAG interface can be used as a backdoor entry to access and exploit devices, also defined as a physical attack. This attack can be used to make products malfunction, modify data, or, in the worst case, stop working. This paper reviews previous successful JTAG exploitations of well-known devices operating online and also reviews some proposed possible solutions to see how they can affect IoT products in a broader sense.
      Citation: Future Internet
      PubDate: 2018-12-03
      DOI: 10.3390/fi10120121
      Issue No: Vol. 10, No. 12 (2018)
  • Future Internet, Vol. 10, Pages 122: A Compact Printed Monopole Antenna
           for WiMAX/WLAN and UWB Applications

    • Authors: Zubin Chen, Baijun Lu, Yanzhou Zhu, Hao Lv
      First page: 122
      Abstract: In this paper, a printed monopole antenna design for WiMAX/WLAN applications in cable-free self-positioning seismograph nodes is proposed. Great improvements were achieved in miniaturizing the antenna and in widening the narrow bandwidth of the high-frequency band. The antenna was fed by a microstrip gradient line and consisted of a triangle, an inverted-F shape, and an M-shaped structure, which was rotated 90° counterclockwise to form a surface-radiating patch. This structure effectively widened the operating bandwidth of the antenna. Excitation led to the generation of two impedance bands of 2.39–2.49 and 4.26–7.99 GHz for a voltage standing wave ratio of less than 2. The two impedance bandwidths were 100 MHz, i.e., 4.08% relative to the center frequency of 2.45 GHz, and 3730 MHz, i.e., 64.31% relative to the center frequency of 5.80 GHz, covering the WiMAX high-frequency band (5.25–5.85 GHz) and the WLAN band (2.4/5.2/5.8). This article describes the design details of the antenna and presents the results of both simulations and experiments that show good agreement. The proposed antenna meets the field-work requirements of cable-less seismograph nodes.
      Citation: Future Internet
      PubDate: 2018-12-13
      DOI: 10.3390/fi10120122
      Issue No: Vol. 10, No. 12 (2018)
  • Future Internet, Vol. 10, Pages 123: Bidirectional Recurrent Neural
           Network Approach for Arabic Named Entity Recognition

    • Authors: Mohammed N. A. Ali, Guanzheng Tan, Aamir Hussain
      First page: 123
      Abstract: Recurrent neural network (RNN) has achieved remarkable success in sequence labeling tasks with memory requirement. RNN can remember previous information of a sequence and can thus be used to solve natural language processing (NLP) tasks. Named entity recognition (NER) is a common task of NLP and can be considered a classification problem. We propose a bidirectional long short-term memory (LSTM) model for this entity recognition task of the Arabic text. The LSTM network can process sequences and relate to each part of it, which makes it useful for the NER task. Moreover, we use pre-trained word embedding to train the inputs that are fed into the LSTM network. The proposed model is evaluated on a popular dataset called “ANERcorp.” Experimental results show that the model with word embedding achieves a high F-score measure of approximately 88.01%.
      Citation: Future Internet
      PubDate: 2018-12-13
      DOI: 10.3390/fi10120123
      Issue No: Vol. 10, No. 12 (2018)
  • Future Internet, Vol. 10, Pages 124: A Method for Filtering Pages by
           Similarity Degree based on Dynamic Programming

    • Authors: Ziyun Deng, Tingqin He
      First page: 124
      Abstract: To obtain the target webpages from many webpages, we proposed a Method for Filtering Pages by Similarity Degree based on Dynamic Programming (MFPSDDP). The method needs to use one of three same relationships proposed between two nodes, so we give the definition of the three same relationships. The biggest innovation of MFPSDDP is that it does not need to know the structures of webpages in advance. First, we address the design ideas with queue and double threads. Then, a dynamic programming algorithm for calculating the length of the longest common subsequence and a formula for calculating similarity are proposed. Further, for obtaining detailed information webpages from 200,000 webpages downloaded from the famous website “”, we choose the same relationship Completely Same Relationship (CSR) and set the similarity threshold to 0.2. The Recall Ratio (RR) of MFPSDDP is in the middle in the four filtering methods compared. When the number of webpages filtered is nearly 200,000, the PR of MFPSDDP is highest in the four filtering methods compared, which can reach 85.1%. The PR of MFPSDDP is 13.3 percentage points higher than the PR of a Method for Filtering Pages by Containing Strings (MFPCS).
      Citation: Future Internet
      PubDate: 2018-12-13
      DOI: 10.3390/fi10120124
      Issue No: Vol. 10, No. 12 (2018)
  • Future Internet, Vol. 10, Pages 125: “Network Sentiment” Framework to
           Improve Security and Privacy for Smart Home

    • Authors: Tommaso Pecorella, Laura Pierucci, Francesca Nizzi
      First page: 125
      Abstract: A Smart Home is characterized by the presence of a huge number of small, low power devices, along with more classical devices. According to the Internet of Things (IoT) paradigm, all of them are expected to be always connected to the Internet in order to provide enhanced services. In this scenario, an attacker can undermine both the network security and the user’s security/privacy. Traditional security measures are not sufficient, because they are too difficult to setup and are either too weak to effectively protect the user or too limiting for the new services effectiveness. The paper suggests to dynamically adapt the security level of the smart home network according to the user perceived risk level what we have called network sentiment analysis. The security level is not fixed, established by a central system (usually by the Internet Service Provider) but can be changed with the users cooperation. The security of the smart home network is improved by a distributed firewalls and Intrusion Detection Systems both to the smart home side as to the Internet Service Provider side. These two parts must cooperate and integrate their actions for reacting dynamically to new and on going threats. Moreover, the level of network sentiment detected can be propagate to nearby home networks (e.g., the smart home networks of the apartments inside a building) to increase/decrease their level of security, thus creating a true in-line Intrusion Prevention System (IPS). The paper also presents a test bed for Smart Home to detect and counteract to different attacks against the IoT sensors, Wi-Fi and Ethernet connections.
      Citation: Future Internet
      PubDate: 2018-12-19
      DOI: 10.3390/fi10120125
      Issue No: Vol. 10, No. 12 (2018)
  • Future Internet, Vol. 10, Pages 103: Initial Coin Offerings and Agile

    • Authors: Simona Ibba, Andrea Pinna, Maria Ilaria Lunesu, Michele Marchesi, Roberto Tonelli
      First page: 103
      Abstract: An ICO (Initial Coin Offering) is an innovative way to fund projects based on blockchain. The funding is based on the selling of tokens by means of decentralized applications called smart contracts written in Solidity, a programming language specific for Ethereum blockchain. The ICOs work in a volatile context and it is crucial that the team is capable of handling constant changes. The Agile methods, proven practices enabling to develop software in presence of changing requirements, could be a means for managing uncertainty. The main goals of this work are to understand software engineering activities related to ICOs, recognize the ICOs developed using Agile methods, and make a comparison between ICOs and Agile ICOs. In addition, we perform a deeper analysis of Agile ICOs concerning project planning, software development, and code features. Our work shows that the roles of the people involved in an ICO can be compared to the typical roles of the SCRUM methodology. The majority of Agile ICOs use tool of testing before storing smart contract on blockchain. Finally, the application of volumetric and complexity software metrics shows that the files of Agile ICOs is on average shorter and less complex than in other smart contracts.
      Citation: Future Internet
      PubDate: 2018-10-23
      DOI: 10.3390/fi10110103
      Issue No: Vol. 10, No. 11 (2018)
  • Future Internet, Vol. 10, Pages 104: RFID Based Manufacturing Process of
           Cloud MES

    • Authors: Chuang Wang, Xu’nan Chen, Abdel-Hamid Ali Soliman, Zhixiang Zhu
      First page: 104
      Abstract: RFID (radio frequency identification) is widely used in the manufacturing processes of enterprises. At the same time, with the advent of the Industry 4.0 era, Manufacturing Execution System (MES) systems began to evolve into cloud MES systems. In this paper, a RFID-based manufacturing process for cloud MES is proposed and a framework manufacturing process fora cloud MES system centered on machine tools is constructed. The process division of the manufacturing process, RFID configuration and cloud processing are analyzed, and other key technologies involved in implementing the framework are briefly discussed. Finally, the effectiveness of a RFID-based manufacturing process of cloud MES is verified by two different types of case analysis namely photovoltaic slice production and garment outsourcing processing.
      Citation: Future Internet
      PubDate: 2018-10-30
      DOI: 10.3390/fi10110104
      Issue No: Vol. 10, No. 11 (2018)
  • Future Internet, Vol. 10, Pages 105: An Integrated Platform for the
           Internet of Things Based on an Open Source Ecosystem

    • Authors: YangQun Li
      First page: 105
      Abstract: The Internet of Things (IoT) is increasingly part of daily life. However, the development of IoT applications still faces many problems, such as heterogeneity, complex management, and other difficulties. In this paper, first, the open source technologies of IoT are surveyed. We compare these technologies from the point of view of different levels of technical requirements, such as device management, data management, communication, intelligent data processing, security and privacy protection; we also look at requirements of application development and deployment. Second, an IoT integrated development platform architecture for IoT applications based on open source ecosystem is proposed and evaluated in an industrial setting. We applied P2P technology to distributed resource management and blockchain-based smart contract mechanics for resource billing management. The results show that the IoT gateway based on an open source ecosystem had a stable and reliable system performance with a certain data size and concurrency scale. These conditions satisfy the application requirements of the IoT in most sensing environments.
      Citation: Future Internet
      PubDate: 2018-10-31
      DOI: 10.3390/fi10110105
      Issue No: Vol. 10, No. 11 (2018)
  • Future Internet, Vol. 10, Pages 106: Design and Implementation of a RFID
           Reader/Router in RFID-WSN Hybrid System

    • Authors: Wusheng Ji, Li Li, Weiwei Zhou
      First page: 106
      Abstract: In order to put Radio Frequency Identification (RFID) and Wireless Sensor Network (WSN) in a hybrid system, this paper presents the design and implementation of a RFID reader/router that can obtain information of both RFID tags and WSN sensor nodes and transmit the information through the WSN to the PC server. The RFID reader and WSN router are combined with both hardware and software. In hardware structure, CC2530 is used as micro controller and RF module for ZigBee wireless communication, and MF RC522 is used as reader RF chip. The software deals with both identity and sensing information and controls the routing. Experiment results show that the RFID reader/router achieves long distance identification, flexibility, scalability, and low cost. It also provides reliable and secured data transmission and broadens the communication range and application scope of RFID readers.
      Citation: Future Internet
      PubDate: 2018-11-03
      DOI: 10.3390/fi10110106
      Issue No: Vol. 10, No. 11 (2018)
  • Future Internet, Vol. 10, Pages 107: Composting as a Service: A Real-World
           IoT Implementation

    • Authors: Yannis Nikoloudakis, Spyridon Panagiotakis, Thrasivoulos Manios, Evangelos Markakis, Evangelos Pallis
      First page: 107
      Abstract: Composting is the delicate procedure of supervised decomposition of organic waste, which gradually transforms waste to nutrient-rich manure. It requires deep knowledge and constant attention by experts to achieve a quality outcome in a timely fashion. Nevertheless, due to the bizarre nature of the materials and the overall procedure, along with the space required and emitted odors, it is required that composting infrastructures and machinery are installed away from residential areas, rendering supervision a very tedious task. Automatic composting machinery is a promising new idea, but still cannot substitute the insightfulness of a human supervisor. In this paper, we introduce COMPosting as a Service (COMPaaS). COMPaaS is a novel cloud service in composition with specialized Internet of Things (IoT)-based composting machinery that allows for unsupervised composting. The focus of this work is on the tiered IT approach that is adopted following the edge-computing paradigm. More specifically, composting machinery, enriched with several sensors and actuators, performs a set of basic routine tasks locally and sends sensor values to a cloud service which performs real-time data analysis and instructs the composting machinery to perform the appropriate actions based on the outcome of the analysis. The overall composting procedure is performed in a completely unsupervised manner, and field evaluation has shown an up to 30% faster outcome in comparison to traditional supervised composting.
      Citation: Future Internet
      PubDate: 2018-11-05
      DOI: 10.3390/fi10110107
      Issue No: Vol. 10, No. 11 (2018)
  • Future Internet, Vol. 10, Pages 108: Quality of Experience in
           Cyber-Physical Social Systems Based on Reinforcement Learning and Game

    • Authors: Eirini Eleni Tsiropoulou, George Kousis, Athina Thanou, Ioanna Lykourentzou, Symeon Papavassiliou
      First page: 108
      Abstract: This paper addresses the problem of museum visitors’ Quality of Experience (QoE) optimization by viewing and treating the museum environment as a cyber-physical social system. To achieve this goal, we harness visitors’ internal ability to intelligently sense their environment and make choices that improve their QoE in terms of which the museum touring option is the best for them and how much time to spend on their visit. We model the museum setting as a distributed non-cooperative game where visitors selfishly maximize their own QoE. In this setting, we formulate the problem of Recommendation Selection and Visiting Time Management (RSVTM) and propose a two-stage distributed algorithm based on game theory and reinforcement learning, which learns from visitor behavior to make on-the-fly recommendation selections that maximize visitor QoE. The proposed framework enables autonomic visitor-centric management in a personalized manner and enables visitors themselves to decide on the best visiting strategies. Experimental results evaluating the performance of the proposed RSVTM algorithm under realistic simulation conditions indicate the high operational effectiveness and superior performance when compared to other recommendation approaches. Our results constitute a practical alternative for museums and exhibition spaces meant to enhance visitor QoE in a flexible, efficient, and cost-effective manner.
      Citation: Future Internet
      PubDate: 2018-11-07
      DOI: 10.3390/fi10110108
      Issue No: Vol. 10, No. 11 (2018)
  • Future Internet, Vol. 10, Pages 109: A Review of DSP-Based Enabling
           Technologies for Cloud Access Networks

    • Authors: Roger Giddings, Xiao Duan, Ehab Al-Rawachy, Mingzhi Mao
      First page: 109
      Abstract: Optical access networks, metro networks and mobile data networks are facing rapidly evolving demands, not only is it essential to satisfy the unyielding need for increased user bandwidths, but future networks must also support the growing wide variation in traffic dynamics and characteristics, due to various emerging technologies, such as cloud-based services, the Internet-of-Things (IoT) and 5G mobile systems, and due to growing trends, such as the proliferation of mobile devices and the rapidly increasing popularity of video-on-demand services. To be cost-effective and commercially sustainable, future optical networks must offer features, such as, dynamic reconfigurability, highly efficient use of network resources, elastic bandwidth provisioning with fine granularity, network sliceabilty and software defined networking (SDN). To meet these requirements Cloud Access Networks (CANs) are proposed which require a number of flexible, adaptive and reconfigurable networking elements. By exploiting digital signal processing (DSP) we have proposed a digital orthogonal filter-based multiplexing technique to implement CANs with multiplexed, independent optical channels at the wavelength, sub-wavelength, and orthogonal sub-band levels. This paper reviews the overall CAN concept, the operating principles of the various CAN network elements and presents an overview of the research work we have undertaken in order to validate the feasibility of the proposed technologies which includes real-time DSP-based demonstrations.
      Citation: Future Internet
      PubDate: 2018-11-15
      DOI: 10.3390/fi10110109
      Issue No: Vol. 10, No. 11 (2018)
  • Future Internet, Vol. 10, Pages 110: Intelligent Environment Monitoring
           System for University Laboratories

    • Authors: Linbo Zhai, Wenwen Jiang
      First page: 110
      Abstract: In recent years, the laboratory security of universities has become an important issue for students and devices. To solve this security issue, this paper proposes an intelligent monitoring system to realize environment detection in university laboratories. The main purpose of this system is to monitor the laboratory environment data in time and improve the laboratory inspection efficiency. The system consists of a single chip microcomputer, which is the core of this system, a sensor function module and GPRS wireless communication, realizing data monitoring and short message warning. Therefore, three features, front-end data acquisition, data wireless transmission and a security alarm, are achieved by the proposed system. The real experiments show that front-end data acquisition is effective, data transmission is reliable, and the alarm message is received in time. Furthermore, the system, with the modified function modules, can be used in other scenarios to detect environments, and thus has a significant applied value in other areas.
      Citation: Future Internet
      PubDate: 2018-11-16
      DOI: 10.3390/fi10110110
      Issue No: Vol. 10, No. 11 (2018)
  • Future Internet, Vol. 10, Pages 111: Neurologist Standard Classification
           of Facial Nerve Paralysis with Deep Neural Networks

    • Authors: Anping Song, Zuoyu Wu, Xuehai Ding, Qian Hu, Xinyi Di
      First page: 111
      Abstract: Facial nerve paralysis (FNP) is the most common form of facial nerve damage, which leads to significant physical pain and abnormal function in patients. Traditional FNP detection methods are based on visual diagnosis, which relies solely on the physician’s assessment. The use of objective measurements can reduce the frequency of errors which are caused by subjective methods. Hence, a fast, accurate, and objective computer method for FNP classification is proposed that uses a single Convolutional neural network (CNN), trained end-to-end directly from images, with only pixels and disease labels as inputs. We trained the CNN using a dataset of 1049 clinical images and divided the dataset into 7 categories based on classification standards with the help of neurologists. We tested its performance against the neurologists’ ground truth, and our results matched the neurologists’ level with 97.5% accuracy.
      Citation: Future Internet
      PubDate: 2018-11-16
      DOI: 10.3390/fi10110111
      Issue No: Vol. 10, No. 11 (2018)
  • Future Internet, Vol. 10, Pages 112: Query Recommendation Using Hybrid
           Query Relevance

    • Authors: Jialu Xu, Feiyue Ye
      First page: 112
      Abstract: With the explosion of web information, search engines have become main tools in information retrieval. However, most queries submitted in web search are ambiguous and multifaceted. Understanding the queries and mining query intention is critical for search engines. In this paper, we present a novel query recommendation algorithm by combining query information and URL information which can get wide and accurate query relevance. The calculation of query relevance is based on query information by query co-concurrence and query embedding vector. Adding the ranking to query-URL pairs can calculate the strength between query and URL more precisely. Empirical experiments are performed based on AOL log. The results demonstrate the effectiveness of our proposed query recommendation algorithm, which achieves superior performance compared to other algorithms.
      Citation: Future Internet
      PubDate: 2018-11-19
      DOI: 10.3390/fi10110112
      Issue No: Vol. 10, No. 11 (2018)
  • Future Internet, Vol. 10, Pages 113: Chinese Text Classification Model
           Based on Deep Learning

    • Authors: Yue Li, Xutao Wang, Pengjian Xu
      First page: 113
      Abstract: Text classification is of importance in natural language processing, as the massive text information containing huge amounts of value needs to be classified into different categories for further use. In order to better classify text, our paper tries to build a deep learning model which achieves better classification results in Chinese text than those of other researchers’ models. After comparing different methods, long short-term memory (LSTM) and convolutional neural network (CNN) methods were selected as deep learning methods to classify Chinese text. LSTM is a special kind of recurrent neural network (RNN), which is capable of processing serialized information through its recurrent structure. By contrast, CNN has shown its ability to extract features from visual imagery. Therefore, two layers of LSTM and one layer of CNN were integrated to our new model: the BLSTM-C model (BLSTM stands for bi-directional long short-term memory while C stands for CNN.) LSTM was responsible for obtaining a sequence output based on past and future contexts, which was then input to the convolutional layer for extracting features. In our experiments, the proposed BLSTM-C model was evaluated in several ways. In the results, the model exhibited remarkable performance in text classification, especially in Chinese texts.
      Citation: Future Internet
      PubDate: 2018-11-20
      DOI: 10.3390/fi10110113
      Issue No: Vol. 10, No. 11 (2018)
  • Future Internet, Vol. 10, Pages 92: Occlusion-Aware Unsupervised Learning
           of Monocular Depth, Optical Flow and Camera Pose with Geometric

    • Authors: Qianru Teng, Yimin Chen, Chen Huang
      First page: 92
      Abstract: We present an occlusion-aware unsupervised neural network for jointly learning three low-level vision tasks from monocular videos: depth, optical flow, and camera motion. The system consists of three different predicting sub-networks simultaneously coupled by combined loss terms and is capable of computing each task independently on test samples. Geometric constraints extracted from scene geometry which have traditionally been used in bundle adjustment or pose-graph optimization are formed as various self-supervisory signals during our end-to-end learning approach. Different from prior works, our image reconstruction loss also takes account of optical flow. Moreover, we impose novel 3D flow consistency constraints over the predictions of all the three tasks. By explicitly modeling occlusion and taking utilization of both 2D and 3D geometry relationships, abundant geometric constraints are formed over estimated outputs, enabling the system to capture both low-level representations and high-level cues to infer thinner scene structures. Empirical evaluation on the KITTI dataset demonstrates the effectiveness and improvement of our approach: (1) monocular depth estimation outperforms state-of-the-art unsupervised methods and is comparable to stereo supervised ones; (2) optical flow prediction ranks top among prior works and even beats supervised and traditional ones especially in non-occluded regions; (3) pose estimation outperforms established SLAM systems under comparable input settings with a reasonable margin.
      Citation: Future Internet
      PubDate: 2018-09-21
      DOI: 10.3390/fi10100092
      Issue No: Vol. 10, No. 10 (2018)
  • Future Internet, Vol. 10, Pages 93: Proactive Caching at the Edge
           Leveraging Influential User Detection in Cellular D2D Networks

    • Authors: Anwar Said, Syed Waqas Haider Shah, Hasan Farooq, Adnan Noor Mian, Ali Imran, Jon Crowcroft
      First page: 93
      Abstract: Caching close to users in a radio access network (RAN) has been identified as a promising method to reduce a backhaul traffic load and minimize latency in 5G and beyond. In this paper, we investigate a novel community detection inspired by a proactive caching scheme for device-to-device (D2D) enabled networks. The proposed scheme builds on the idea that content generated/accessed by influential users is more probable to become popular and thus can be exploited for pro-caching. We use a Clustering Coefficient based Genetic Algorithm (CC-GA) for community detection to discover a group of cellular users present in close vicinity. We then use an Eigenvector Centrality measure to identify the influential users with respect to the community structure, and the content associated to it is then used for pro-active caching using D2D communications. The numerical results show that, compared to reactive caching, where historically popular content is cached, depending on cache size, load and number of requests, up to 30% more users can be satisfied using a proposed scheme while achieving significant reduction in backhaul traffic load.
      Citation: Future Internet
      PubDate: 2018-09-21
      DOI: 10.3390/fi10100093
      Issue No: Vol. 10, No. 10 (2018)
  • Future Internet, Vol. 10, Pages 94: Influence of Crowd Participation
           Features on Mobile Edge Computing

    • Authors: Peiyan Yuan, Xiaoxiao Pang, Xiaoyan Zhao
      First page: 94
      Abstract: Mobile edge computing is a new communication paradigm, which stores content close to the end users, so as to reduce the backhaul delay and alleviate the traffic load of the backbone networks. Crowd participation is one of the most striking features of this technology, and it enables numerous interesting applications. The dynamics of crowd participation offer unprecedented opportunities for both content caching and data forwarding. In this paper, we investigate the influence of the dynamics of crowd participation, from the perspective of opportunistic caching and forwarding, and discuss how we can exploit such opportunities to allocate content and select relays efficiently. Some existing issues in this emerging research area are also discussed.
      Citation: Future Internet
      PubDate: 2018-09-25
      DOI: 10.3390/fi10100094
      Issue No: Vol. 10, No. 10 (2018)
  • Future Internet, Vol. 10, Pages 95: Chinese Event Extraction Based on
           Attention and Semantic Features: A Bidirectional Circular Neural Network

    • Authors: Yue Wu, Junyi Zhang
      First page: 95
      Abstract: Chinese event extraction uses word embedding to capture similarity, but suffers when handling previously unseen or rare words. From the test, we know that characters may provide some information that we cannot obtain in words, so we propose a novel architecture for combining word representations: character–word embedding based on attention and semantic features. By using an attention mechanism, our method is able to dynamically decide how much information to use from word or character level embedding. With the semantic feature, we can obtain some more information about a word from the sentence. We evaluate different methods on the CEC Corpus, and this method is found to improve performance.
      Citation: Future Internet
      PubDate: 2018-09-26
      DOI: 10.3390/fi10100095
      Issue No: Vol. 10, No. 10 (2018)
  • Future Internet, Vol. 10, Pages 96: A Modified BA Anti-Collision Protocol
           for Coping with Capture Effect and Interference in RFID Systems

    • Authors: Isam A. Hussein, Basil H. Jasim, Ramzy S. Ali
      First page: 96
      Abstract: Radio frequency identification (RFID) technology has widely been used in the last few years. Its applications focus on auto identification, tracking, and data capturing issues. However, RFID suffers from the main problem of tags collision when multiple tags simultaneously respond to the reader request. Many protocols were proposed to solve the collision problems with good identification efficiency and an acceptable time delay, such as the blocking anti-collision protocol (BA). Nevertheless, most of these protocols assumed that the RFID reader could decode the tag’s signal only when there was one tag responding to the reader request once each time. Hence, they ignored the phenomenon of the capture effect, which results in identifying the tag with the stronger signal as the multiple tags simultaneously respond. As a result, many tags will not be identified under the capture effect. Therefore, the purpose of this paper is to take the capture effect phenomenon into consideration in order to modify the blocking BA protocol to ensure a full read rate, i.e., identifying all the tags in the frame without losing any tag. Moreover, the modifications include distinguishing between collision and interference responses (for the period of staying tags) in the noisy environments, for the purpose of enhancing the efficiency of the identification. Finally, the simulation and analytical results show that our modifications and MBA protocol outperform the previous protocols in the same field, such as generalized query tree protocols (GQT1 and GQT2), general binary tree (GBT), and tweaked binary tree (TBT).
      Citation: Future Internet
      PubDate: 2018-10-01
      DOI: 10.3390/fi10100096
      Issue No: Vol. 10, No. 10 (2018)
  • Future Internet, Vol. 10, Pages 97: The Effect of Customer Participation
           Types on Online Recovery Satisfaction: A Mental Accounting Perspective

    • Authors: Yu Zhang, Bingjia Shao
      First page: 97
      Abstract: With the high popularity of the Internet, online trading has gradually replaced the traditional shopping model and extended to every corner of social life. However, online trading cannot avoid failures; thus, understanding how firms can best recover customers in online contexts to keep customer loyalty is very important. This study investigates the mechanisms by which customer participation types (physical, mental, and emotional) promote customers’ perceived justice and post-recovery satisfaction from a mental accounting perspective. Furthermore, the moderating effects of two modes of online apology speech acts (direct and indirect) on customer participation and perceived justice are investigated. A total of 1083 Chinese tourists who have purchased a Wi-Fi rental service in the past year were contacted according to the database provided by two travel agencies, and 329 stated having experienced an online recovery service and participated in the survey; 297 valid questionnaires were collected. Among them, 48.82% were males and 51.18% females. Most of the respondents were aged 20–35 years. By carrying out data analysis by partial least squares structural equation modeling (PLS-SEM) using SmartPLS, the results show that, first, only mental and physical participation can enhance perceived justice, while emotional participation does not influence perceived justice. Second, the positive influence of mental participation on perceived justice is most significant. Third, only when the service staff adopts the indirect mode to express an online apology, mental and physical participation can enhance perceived justice.
      Citation: Future Internet
      PubDate: 2018-10-03
      DOI: 10.3390/fi10100097
      Issue No: Vol. 10, No. 10 (2018)
  • Future Internet, Vol. 10, Pages 98: Structured Data REST Protocol for End
           to End Data Mashup

    • Authors: Prakash Hardaha, Shailendra Singh
      First page: 98
      Abstract: Due to the exponential growth of the data and its services, visiting multiple webs/apps by a user raises three issues—(1) consumption of extra bytes; (2) time killing process of surfing inside the webs/apps; (3) tedious task of remembering address of webs/apps with their credentials. The data mashup is a set of techniques and user-friendly approaches which not only resolves above issues but also allows ordinary user to fetch required data from multiple disparate data sources and to create the integrated view in his defined digital place. In this paper, we have proposed an extension of existing REST protocol called Structured Data REST (SDRest) protocol and user-friendly novel approach which allows even ordinary users to develop end to end data mashup, using the innovative concept of Structured Data Mashup Box (SDMB) and One Time Configuration (OTC)-Any Time Access (ATA) models. Our implementation shows that pre-mashup configuration can easily be performed by an ordinary user and an integrated user interface view of end user data mashup can be created without any technical knowledge or programming. We have also evaluated the proposed work by comparing it with some of the related works and found that the proposed work has developed user friendly configurable approach using the current state of the art techniques to involve not only the ordinary user but also the mashup service provider and the data service provider to develop public, private and hybrid data mashup.
      Citation: Future Internet
      PubDate: 2018-10-04
      DOI: 10.3390/fi10100098
      Issue No: Vol. 10, No. 10 (2018)
  • Future Internet, Vol. 10, Pages 99: The Optimization of Marine Diesel
           Engine Rotational Speed Control Process by Fuzzy Logic Control Based on
           Particle Swarm Optimization Algorithm

    • Authors: Tien Tran
      First page: 99
      Abstract: The marine main diesel engine rotational speed automatic control plays a significant role in determining the optimal main diesel engine speed under impacting on navigation environment conditions. In this article, the application of fuzzy logic control theory for main diesel engine speed control has been associated with Particle Swarm Optimization (PSO). Firstly, the controller is designed according to fuzzy logic control theory. Secondly, the fuzzy logic controller will be optimized by Particle Swarm Optimization (PSO) in order to obtain the optimal adjustment of the membership functions only. Finally, the fuzzy logic controller has been completely innovated by Particle Swarm Optimization algorithm. The study results will be represented under digital simulation form, as well as comparison between traditional fuzzy logic controller with fuzzy logic control–particle swarm optimization speed controller being obtained.
      Citation: Future Internet
      PubDate: 2018-10-04
      DOI: 10.3390/fi10100099
      Issue No: Vol. 10, No. 10 (2018)
  • Future Internet, Vol. 10, Pages 100: Agile Service Engineering in the
           Industrial Internet of Things

    • Authors: Thomas Usländer, Thomas Batz
      First page: 100
      Abstract: The emerging Industrial Internet of Things (IIoT) will not only leverage new and potentially disruptive business models but will also change the way software applications will be analyzed and designed. Agility is a need in a systematic service engineering as well as a co-design of requirements and architectural artefacts. Functional and non-functional requirements of IT users (in smart manufacturing mostly from the disciplines of mechanical engineering and electrical engineering) need to be mapped to the capabilities and interaction patterns of emerging IIoT service platforms, not to forget the corresponding information models. The capabilities of such platforms are usually described, structured, and formalized by software architects and software engineers. However, their technical descriptions are far away from the thinking and the thematic terms of end-users. This complicates the transition from requirements analysis to system design, and hence the re-use of existing and the design of future platform capabilities. Current software engineering methodologies do not systematically cover these interlinked and two-sided aspects. The article describes in a comprehensive manner how to close this gap with the help of a service-oriented analysis and design methodology entitled SERVUS (also mentioned in ISO 19119 Annex D) and a corresponding Web-based Platform Engineering Information System (PEIS).
      Citation: Future Internet
      PubDate: 2018-10-09
      DOI: 10.3390/fi10100100
      Issue No: Vol. 10, No. 10 (2018)
  • Future Internet, Vol. 10, Pages 101: Reframing HRI Design Opportunities
           for Social Robots: Lessons Learnt from a Service Robotics Case Study
           Approach Using UX for HRI

    • Authors: Sara Khan, Claudio Germak
      First page: 101
      Abstract: Over the last few decades, semi-autonomous machine’s technology started to promote awareness towards the importance of human–robot interaction (HRI) for improving daily activities. More affordable social robots are being commercially released and in order to implement viable applications of HRI, a combination human-computer interaction and user experience methodologies could play a pivotal role in assessing new scenarios and evaluating new investigations. However, literature shows that it is still challenging to reach an optimal user experience with robotic companions. The aim of the study was to determine the chance to enhance the user experience with a semi-autonomous social robot, using user experience and human–computer interaction methodologies. In this study, a social robotic companion has been developed and prototyped in order to be adopted in a specific public environment such as a company workspace. The challenges emerged from this peculiar environment triggered the need for a more productive and comfortable office for the employees, and, at the same time, the usability, acceptance and likeability of the robotic companion have been evaluated. The results emphasize that, since HRI is highly interdisciplinary, the benefits of combining approaches from other fields could positively benefit from a meaningful social interaction with the users.
      Citation: Future Internet
      PubDate: 2018-10-10
      DOI: 10.3390/fi10100101
      Issue No: Vol. 10, No. 10 (2018)
  • Future Internet, Vol. 10, Pages 102: An Environmentally Aware Scheme of
           Wireless Sensor Networks for Forest Fire Monitoring and Detection

    • Authors: Yi-Han Xu, Qiu-Ya Sun, Yu-Tong Xiao
      First page: 102
      Abstract: Forest fires are a fatal threat to environmental degradation. Wireless sensor networks (WSNs) are regarded as a promising candidate for forest fire monitoring and detection since they enable real-time monitoring and early detection of fire threats in an efficient way. However, compared to conventional surveillance systems, WSNs operate under a set of unique resource constraints, including limitations with respect to transmission range, energy supply and computational capability. Considering that long transmission distance is inevitable in harsh geographical features such as woodland and shrubland, energy-efficient designs of WSNs are crucial for effective forest fire monitoring and detection systems. In this paper, we propose a novel framework that harnesses the benefits of WSNs for forest fire monitoring and detection. The framework employs random deployment, clustered hierarchy network architecture and environmentally aware protocols. The goal is to accurately detect a fire threat as early as possible while maintaining a reasonable energy consumption level. ns-2-based simulation validates that the proposed framework outperforms the conventional schemes in terms of detection delay and energy consumption.
      Citation: Future Internet
      PubDate: 2018-10-19
      DOI: 10.3390/fi10100102
      Issue No: Vol. 10, No. 10 (2018)
School of Mathematical and Computer Sciences
Heriot-Watt University
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