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Future Internet
Journal Prestige (SJR): 0.219
Citation Impact (citeScore): 1
Number of Followers: 140  

  This is an Open Access Journal Open Access journal
ISSN (Print) 1999-5903
Published by MDPI Homepage  [215 journals]
  • Future Internet, Vol. 11, Pages 83: A Study on Join Operations in MongoDB
           Preserving Collections Data Models for Future Internet Applications

    • Authors: Antonio Celesti, Maria Fazio, Massimo Villari
      First page: 83
      Abstract: Presently, we are observing an explosion of data that need to be stored and processed over the Internet, and characterized by large volume, velocity and variety. For this reason, software developers have begun to look at NoSQL solutions for data storage. However, operations that are trivial in traditional Relational DataBase Management Systems (DBMSs) can become very complex in NoSQL DBMSs. This is the case of the join operation to establish a connection between two or more DB structures, whose construct is not explicitly available in many NoSQL databases. As a consequence, the data model has to be changed or a set of operations have to be performed to address particular queries on data. Thus, open questions are: how do NoSQL solutions work when they have to perform join operations on data that are not natively supported' What is the quality of NoSQL solutions in such cases' In this paper, we deal with such issues specifically considering one of the major NoSQL document oriented DB available on the market: MongoDB. In particular, we discuss an approach to perform join operations at application layer in MongoDB that allows us to preserve data models. We analyse performance of the proposes approach discussing the introduced overhead in comparison with SQL-like DBs.
      Citation: Future Internet
      PubDate: 2019-03-27
      DOI: 10.3390/fi11040083
      Issue No: Vol. 11, No. 4 (2019)
  • Future Internet, Vol. 11, Pages 84: Cyber Dating Abuse and Masculine
           Gender Norms in a Sample of Male Adults

    • Authors: Beatriz Villora, Santiago Yubero, Raúl Navarro
      First page: 84
      Abstract: Gender role norms have been widely studied in the offline partner violence context. Different studies have indicated that internalizing these norms was associated with dating violence. However, very few research works have analyzed this relation in forms of aggression against partners and former partners using information and communication technologies (ICT). The objective of the present study was to examine the co-occurrence of cyber dating abuse by analyzing the extent to which victimization and perpetration overlap, and by analyzing the differences according to conformity to the masculine gender norms between men who are perpetrators or victims of cyber dating abuse. The participants were 614 male university students, and 26.5% of the sample reported having been a victim and perpetrator of cyber dating abuse. Nonetheless, the regression analyses did not reveal any statistically significant association between conformity to masculine gender norms and practicing either perpetration or victimization by cyber dating abuse.
      Citation: Future Internet
      PubDate: 2019-03-28
      DOI: 10.3390/fi11040084
      Issue No: Vol. 11, No. 4 (2019)
  • Future Internet, Vol. 11, Pages 85: A Robust Security Architecture for
           SDN-Based 5G Networks

    • Authors: Jiaying Yao, Zhigeng Han, Muhammad Sohail, Liangmin Wang
      First page: 85
      Abstract: 5G is the latest generation of cellular mobile communications. Due to its significant advantage in high data rate, reduced latency and massive device connectivity, the 5G network plays a vital role in today’s commercial telecommunications networks. However, the 5G network also faces some challenges when used in practice. This is because it consists of various diverse ingredients, termed heterogeneity. The heterogeneity of the 5G network has two consequences: first, it prevents us to use this technology in a uniform way, preventing the wide use of 5G technology; second, it complicates the structure of the 5G network, making it hard to monitor what is going on in a 5G network. To break through this limitation, researchers have worked in this field and design their own protocol, in which software-defined networking (SDN) is one key design concept. By separating control and data plane, SDN can make the 5G network functional and programmable, such that we can handle the heterogeneity in traditional 5G networks. In light of this, we say that SDN-5G network is attractive, but its advantages are not free. The intelligence centralization used in SDN has its own drawbacks when it comes to security. To break through this limitation, we propose a robust security architecture for SDN-based 5G Networks. To find the illegal request from malicious attackers, we add extra cryptographic authentication, termed synchronize secret. The basic idea of our scheme is leveraging preload secrets to differ attacks from regular network communications. The simulation results indicate that our work can completely handle the security problem from SDN with a low disconnect rate of 0.01%, which is much better than that from state of the art.
      Citation: Future Internet
      PubDate: 2019-03-28
      DOI: 10.3390/fi11040085
      Issue No: Vol. 11, No. 4 (2019)
  • Future Internet, Vol. 11, Pages 86: Tax Fraud Detection through Neural
           Networks: An Application Using a Sample of Personal Income Taxpayers

    • Authors: César Pérez López, María Jesús Delgado Rodríguez, Sonia de Lucas Santos
      First page: 86
      Abstract: The goal of the present research is to contribute to the detection of tax fraud concerning personal income tax returns (IRPF, in Spanish) filed in Spain, through the use of Machine Learning advanced predictive tools, by applying Multilayer Perceptron neural network (MLP) models. The possibilities springing from these techniques have been applied to a broad range of personal income return data supplied by the Institute of Fiscal Studies (IEF). The use of the neural networks enabled taxpayer segmentation as well as calculation of the probability concerning an individual taxpayer’s propensity to attempt to evade taxes. The results showed that the selected model has an efficiency rate of 84.3%, implying an improvement in relation to other models utilized in tax fraud detection. The proposal can be generalized to quantify an individual’s propensity to commit fraud with regards to other kinds of taxes. These models will support tax offices to help them arrive at the best decisions regarding action plans to combat tax fraud.
      Citation: Future Internet
      PubDate: 2019-03-30
      DOI: 10.3390/fi11040086
      Issue No: Vol. 11, No. 4 (2019)
  • Future Internet, Vol. 11, Pages 87: Information Quality or Entities’
           Interactivity' Understanding the Determinants of Social Network-Based
           Brand Community Participation

    • Authors: Haichuan Zhao
      First page: 87
      Abstract: The customer’s participation is important to the survival of a brand community. By drawing on flow theory, this research identified the most important factors that motivate the customers’ participation intention than others in a social network-based brand community. Data were collected from the Sina micro-blog. This study adopted two different but complementary methods to analyse the conceptual model: Structure equation model (SEM) and fuzzy set qualitative analysis (fsQCA). Results support most of the research hypothesis. Specifically, the findings obtained from the fsQCA indicate that information quality and platform-interactivity are necessary conditions that encourage the customers’ participation in a brand community.
      Citation: Future Internet
      PubDate: 2019-04-01
      DOI: 10.3390/fi11040087
      Issue No: Vol. 11, No. 4 (2019)
  • Future Internet, Vol. 11, Pages 88: An Optimal Energy-Saving Strategy for
           Home Energy Management Systems with Bounded Customer Rationality

    • Authors: Guoying Lin, Yuyao Yang, Feng Pan, Sijian Zhang, Fen Wang, Shuai Fan
      First page: 88
      Abstract: With the development of techniques, such as the Internet of Things (IoT) and edge computing, home energy management systems (HEMS) have been widely implemented to improve the electric energy efficiency of customers. In order to automatically optimize electric appliances’ operation schedules, this paper considers how to quantitatively evaluate a customer’s comfort satisfaction in energy-saving programs, and how to formulate the optimal energy-saving model based on this satisfaction evaluation. First, the paper categorizes the utility functions of current electric appliances into two types; time-sensitive utilities and temperature-sensitive utilities, which cover nearly all kinds of electric appliances in HEMS. Furthermore, considering the bounded rationality of customers, a novel concept called the energy-saving cost is defined by incorporating prospect theory in behavioral economics into general utility functions. The proposed energy-saving cost depicts the comfort loss risk for customers when their HEMS schedules the operation status of appliances, which is able to be set by residents as a coefficient in the automatic energy-saving program. An optimization model is formulated based on minimizing energy consumption. Because the energy-saving cost has already been evaluated in the context of the satisfaction of customers, the formulation of the optimization program is very simple and has high computational efficiency. The case study included in this paper is first performed on a general simulation system. Then, a case study is set up based on real field tests from a pilot project in Guangdong province, China, in which air-conditioners, lighting, and some other popular electric appliances were included. The total energy-saving rate reached 65.5% after the proposed energy-saving program was deployed in our project. The benchmark test shows our optimal strategy is able to considerably save electrical energy for residents while ensuring customers’ comfort satisfaction is maintained.
      Citation: Future Internet
      PubDate: 2019-04-02
      DOI: 10.3390/fi11040088
      Issue No: Vol. 11, No. 4 (2019)
  • Future Internet, Vol. 11, Pages 89: Social Engineering Attacks: A Survey

    • Authors: Fatima Salahdine, Naima Kaabouch
      First page: 89
      Abstract: The advancements in digital communication technology have made communication between humans more accessible and instant. However, personal and sensitive information may be available online through social networks and online services that lack the security measures to protect this information. Communication systems are vulnerable and can easily be penetrated by malicious users through social engineering attacks. These attacks aim at tricking individuals or enterprises into accomplishing actions that benefit attackers or providing them with sensitive data such as social security number, health records, and passwords. Social engineering is one of the biggest challenges facing network security because it exploits the natural human tendency to trust. This paper provides an in-depth survey about the social engineering attacks, their classifications, detection strategies, and prevention procedures.
      Citation: Future Internet
      PubDate: 2019-04-02
      DOI: 10.3390/fi11040089
      Issue No: Vol. 11, No. 4 (2019)
  • Future Internet, Vol. 11, Pages 90: Ant Colony Optimization Task
           Scheduling Algorithm for SWIM Based on Load Balancing

    • Authors: Gang Li, Zhijun Wu
      First page: 90
      Abstract: This paper focuses on the load imbalance problem in System Wide Information Management (SWIM) task scheduling. In order to meet the quality requirements of users for task completion, we studied large-scale network information system task scheduling methods. Combined with the traditional ant colony optimization (ACO) algorithm, using the hardware performance quality index and load standard deviation function of SWIM resource nodes to update the pheromone, a SWIM ant colony task scheduling algorithm based on load balancing (ACTS-LB) is presented in this paper. The experimental simulation results show that the ACTS-LB algorithm performance is better than the traditional min-min algorithm, ACO algorithm and particle swarm optimization (PSO) algorithm. It not only reduces the task execution time and improves the utilization of system resources, but also can maintain SWIM in a more load balanced state.
      Citation: Future Internet
      PubDate: 2019-04-02
      DOI: 10.3390/fi11040090
      Issue No: Vol. 11, No. 4 (2019)
  • Future Internet, Vol. 11, Pages 91: Dynamic Gesture Recognition Based on
           MEMP Network

    • Authors: Xinyu Zhang, Xiaoqiang Li
      First page: 91
      Abstract: In recent years, gesture recognition has been used in many fields, such as games, robotics and sign language recognition. Human computer interaction (HCI) has been significantly improved by the development of gesture recognition, and now gesture recognition in video is an important research direction. Because each kind of neural network structure has its limitation, we proposed a neural network with alternate fusion of 3D CNN and ConvLSTM, which we called the Multiple extraction and Multiple prediction (MEMP) network. The main feature of the MEMP network is to extract and predict the temporal and spatial feature information of gesture video multiple times, which enables us to obtain a high accuracy rate. In the experimental part, three data sets (LSA64, SKIG and Chalearn 2016) are used to verify the performance of network. Our approach achieved high accuracy on those data sets. In the LSA64, the network achieved an identification rate of 99.063%. In SKIG, this network obtained the recognition rates of 97.01% and 99.02% in the RGB part and the rgb-depth part. In Chalearn 2016, the network achieved 74.57% and 78.85% recognition rates in RGB part and rgb-depth part respectively.
      Citation: Future Internet
      PubDate: 2019-04-03
      DOI: 10.3390/fi11040091
      Issue No: Vol. 11, No. 4 (2019)
  • Future Internet, Vol. 11, Pages 92: Epidemic Spreading in Urban Areas
           Using Agent-Based Transportation Models

    • Authors: Jürgen Hackl, Thibaut Dubernet
      First page: 92
      Abstract: Human mobility is a key element in the understanding of epidemic spreading. Thus, correctly modeling and quantifying human mobility is critical for studying large-scale spatial transmission of infectious diseases and improving epidemic control. In this study, a large-scale agent-based transport simulation (MATSim) is linked with a generic epidemic spread model to simulate the spread of communicable diseases in an urban environment. The use of an agent-based model allows reproduction of the real-world behavior of individuals’ daily path in an urban setting and allows the capture of interactions among them, in the form of a spatial-temporal social network. This model is used to study seasonal influenza outbreaks in the metropolitan area of Zurich, Switzerland. The observations of the agent-based models are compared with results from classical SIR models. The model presented is a prototype that can be used to analyze multiple scenarios in the case of a disease spread at an urban scale, considering variations of different model parameters settings. The results of this simulation can help to improve comprehension of the disease spread dynamics and to take better steps towards the prevention and control of an epidemic.
      Citation: Future Internet
      PubDate: 2019-04-08
      DOI: 10.3390/fi11040092
      Issue No: Vol. 11, No. 4 (2019)
  • Future Internet, Vol. 11, Pages 93: A Smart Cities LoRaWAN Network Based
           on Autonomous Base Stations (BS) for Some Countries with Limited Internet

    • Authors: Pape Abdoulaye Barro, Marco Zennaro, Jules Degila, Ermanno Pietrosemoli
      First page: 93
      Abstract: An increasing number of implementations of IoT for development use the LoRaWAN protocol as many of them leverage the free network and application servers provided by The Things Networks (TTN) to fulfill their needs. Unfortunately, in some countries in Sub-Saharan Africa and South Asia, Internet access cannot be taken for granted, therefore, TTN might not be available. Moreover, low-cost and low-power consumption options devices are the most sustainable ones. In this paper, we propose a LoRaWAN network with autonomous base stations that can work without Internet connectivity for essential services, while being able to provide additional features whenever Internet access becomes available, even in an intermittent fashion. Security and privacy are preserved, with support for mobile nodes.
      Citation: Future Internet
      PubDate: 2019-04-08
      DOI: 10.3390/fi11040093
      Issue No: Vol. 11, No. 4 (2019)
  • Future Internet, Vol. 11, Pages 94: A Review of Machine Learning and IoT
           in Smart Transportation

    • Authors: Fotios Zantalis, Grigorios Koulouras, Sotiris Karabetsos, Dionisis Kandris
      First page: 94
      Abstract: With the rise of the Internet of Things (IoT), applications have become smarter and connected devices give rise to their exploitation in all aspects of a modern city. As the volume of the collected data increases, Machine Learning (ML) techniques are applied to further enhance the intelligence and the capabilities of an application. The field of smart transportation has attracted many researchers and it has been approached with both ML and IoT techniques. In this review, smart transportation is considered to be an umbrella term that covers route optimization, parking, street lights, accident prevention/detection, road anomalies, and infrastructure applications. The purpose of this paper is to make a self-contained review of ML techniques and IoT applications in Intelligent Transportation Systems (ITS) and obtain a clear view of the trends in the aforementioned fields and spot possible coverage needs. From the reviewed articles it becomes profound that there is a possible lack of ML coverage for the Smart Lighting Systems and Smart Parking applications. Additionally, route optimization, parking, and accident/detection tend to be the most popular ITS applications among researchers.
      Citation: Future Internet
      PubDate: 2019-04-10
      DOI: 10.3390/fi11040094
      Issue No: Vol. 11, No. 4 (2019)
  • Future Internet, Vol. 11, Pages 95: Influence Maximization in Social
           Network Considering Memory Effect and Social Reinforcement Effect

    • Authors: Wang, Zhu, Liu, Wang
      First page: 95
      Abstract: Social networks have attracted a lot of attention as novel information or advertisement diffusion media for viral marketing. Influence maximization describes the problem of finding a small subset of seed nodes in a social network that could maximize the spread of influence. A lot of algorithms have been proposed to solve this problem. Recently, in order to achieve more realistic viral marketing scenarios, some constrained versions of influence maximization, which consider time constraints, budget constraints and so on, have been proposed. However, none of them considers the memory effect and the social reinforcement effect, which are ubiquitous properties of social networks. In this paper, we define a new constrained version of the influence maximization problem that captures the social reinforcement and memory effects. We first propose a novel propagation model to capture the dynamics of the memory and social reinforcement effects. Then, we modify two baseline algorithms and design a new algorithm to solve the problem under the model. Experiments show that our algorithm achieves the best performance with relatively low time complexity. We also demonstrate that the new version captures some important properties of viral marketing in social networks, such as such as social reinforcements, and could explain some phenomena that cannot be explained by existing influence maximization problem definitions.
      Citation: Future Internet
      PubDate: 2019-04-11
      DOI: 10.3390/fi11040095
      Issue No: Vol. 11, No. 4 (2019)
  • Future Internet, Vol. 11, Pages 96: An Improved Approach for Text
           Sentiment Classification Based on a Deep Neural Network via a Sentiment
           Attention Mechanism

    • Authors: Li, Liu, Zhang, Liu
      First page: 96
      Abstract: Text sentiment analysis is an important but challenging task. Remarkable success has been achieved along with the wide application of deep learning methods, but deep learning methods dealing with text sentiment classification tasks cannot fully exploit sentiment linguistic knowledge, which hinders the development of text sentiment analysis. In this paper, we propose a sentiment-feature-enhanced deep neural network (SDNN) to address the problem by integrating sentiment linguistic knowledge into a deep neural network via a sentiment attention mechanism. Specifically, first we introduce a novel sentiment attention mechanism to help select the crucial sentiment-word-relevant context words by leveraging the sentiment lexicon in an attention mechanism, which bridges the gap between traditional sentiment linguistic knowledge and current popular deep learning methods. Second, we develop an improved deep neural network to extract sequential correlation information and text local features by combining bidirectional gated recurrent units with a convolutional neural network, which further enhances the ability of comprehensive text representation learning. With this design, the SDNN model can generate a powerful semantic representation of text to improve the performance of text sentiment classification tasks. Extensive experiments were conducted to evaluate the effectiveness of the proposed SDNN model on two real-world datasets with a binary-sentiment-label and a multi-sentiment-label. The experimental results demonstrated that the SDNN achieved substantially better performance than the strong competitors for text sentiment classification tasks.
      Citation: Future Internet
      PubDate: 2019-04-11
      DOI: 10.3390/fi11040096
      Issue No: Vol. 11, No. 4 (2019)
  • Future Internet, Vol. 11, Pages 97: A Method of Bus Network Optimization
           Based on Complex Network and Beidou Vehicle Location

    • Authors: Peixin Dong, Dongyuan Li, Jianping Xing, Haohui Duan, Yong Wu
      First page: 97
      Abstract: Aiming at the problems of poor time performance and accuracy in bus stops network optimization, this paper proposes an algorithm based on complex network and graph theory and Beidou Vehicle Location to measure the importance of bus stops. This method narrows the scope of points and edges to be optimized and is applied to the Jinan bus stop network. In this method, the bus driving efficiency, which can objectively reflect actual road conditions, is taken as the weight of the connecting edges in the network, and the network is optimized through the network efficiency. The experimental results show that, compared with the original network, the optimized network time performance is good and the optimized network bus driving efficiency is improved.
      Citation: Future Internet
      PubDate: 2019-04-15
      DOI: 10.3390/fi11040097
      Issue No: Vol. 11, No. 4 (2019)
  • Future Internet, Vol. 11, Pages 98: FollowMe: One Social Importance-Based
           Collaborative Scheme in MONs

    • Authors: Peiyan Yuan, Xiaoxiao Pang, Ping Liu, En Zhang
      First page: 98
      Abstract: The performance of mobile opportunistic networks mainly relies on collaboration among nodes. Thus far, researchers have ignored the influence of node sociality on the incentive process, leading to poor network performance. Considering the fact that followers always imitate the behavior of superstars, this paper proposes FollowMe, which integrates the social importance of nodes with evolutionary game theory to improve the collaborative behavior of nodes. First, we use the prisoner’s dilemma model to establish the matrix of game gains between nodes. Second, we introduce the signal reference as a game rule between nodes. The number of nodes choosing different strategies in a game round is used to calculate the cumulative income of the node in combination with the probability formula. Finally, the Fermi function is used to determine whether the node updates the strategy. The simulation results show that, compared with the random update rule, the proposed strategy is more capable of promoting cooperative behavior between nodes to improve the delivery rate of data packets.
      Citation: Future Internet
      PubDate: 2019-04-17
      DOI: 10.3390/fi11040098
      Issue No: Vol. 11, No. 4 (2019)
  • Future Internet, Vol. 11, Pages 99: Wireless Mesh Networking: An
           IoT-Oriented Perspective Survey on Relevant Technologies

    • Authors: Antonio Cilfone, Luca Davoli, Laura Belli, Gianluigi Ferrari
      First page: 99
      Abstract: The Internet of Things (IoT), being a “network of networks”, promises to allow billions of humans and machines to interact with each other. Owing to this rapid growth, the deployment of IoT-oriented networks based on mesh topologies is very attractive, thanks to their scalability and reliability (in the presence of failures). In this paper, we provide a comprehensive survey of the following relevant wireless technologies: IEEE 802.11, Bluetooth, IEEE 802.15.4-oriented, and Sub-GHz-based LoRa. Our goal is to highlight how various communication technologies may be suitable for mesh networking, either providing a native support or being adapted subsequently. Hence, we discuss how these wireless technologies, being either standard or proprietary, can adapt to IoT scenarios (e.g., smart cities and smart agriculture) in which the heterogeneity of the involved devices is a key feature. Finally, we provide reference use cases involving all the analyzed mesh-oriented technologies.
      Citation: Future Internet
      PubDate: 2019-04-17
      DOI: 10.3390/fi11040099
      Issue No: Vol. 11, No. 4 (2019)
  • Future Internet, Vol. 11, Pages 100: Edge Computing: A Survey On the
           Hardware Requirements in the Internet of Things World

    • Authors: Maurizio Capra, Riccardo Peloso, Guido Masera, Massimo Ruo Roch, Maurizio Martina
      First page: 100
      Abstract: In today’s world, ruled by a great amount of data and mobile devices, cloud-based systems are spreading all over. Such phenomenon increases the number of connected devices, broadcast bandwidth, and information exchange. These fine-grained interconnected systems, which enable the Internet connectivity for an extremely large number of facilities (far beyond the current number of devices) go by the name of Internet of Things (IoT). In this scenario, mobile devices have an operating time which is proportional to the battery capacity, the number of operations performed per cycle and the amount of exchanged data. Since the transmission of data to a central cloud represents a very energy-hungry operation, new computational paradigms have been implemented. The computation is not completely performed in the cloud, distributing the power load among the nodes of the system, and data are compressed to reduce the transmitted power requirements. In the edge-computing paradigm, part of the computational power is moved toward data collection sources, and, only after a first elaboration, collected data are sent to the central cloud server. Indeed, the “edge” term refers to the extremities of systems represented by IoT devices. This survey paper presents the hardware architectures of typical IoT devices and sums up many of the low power techniques which make them appealing for a large scale of applications. An overview of the newest research topics is discussed, besides a final example of a complete functioning system, embedding all the introduced features.
      Citation: Future Internet
      PubDate: 2019-04-23
      DOI: 10.3390/fi11040100
      Issue No: Vol. 11, No. 4 (2019)
  • Future Internet, Vol. 11, Pages 54: SAES: An Introduction to Self-Adapting
           Exploratory Structures

    • Authors: Giovanni Maria Sacco
      First page: 54
      Abstract: Self-adapting exploratory structures (SAESs) are the basic components of exploratory search. They are abstract structures which allow searching or querying of an information base and summarizing of results using a uniform representation. A definition and a characterization of SAES is given, as well as a discussion of structures that are SAES or can be modified in order to become SAES. These include dynamic taxonomies (also known as faceted search), tag clouds, continuous sliders, geographic maps, and dynamic clustering methods, such as Scatter-Gather. Finally, the integration of these structures into a single interface is discussed.
      Citation: Future Internet
      PubDate: 2019-02-26
      DOI: 10.3390/fi11030054
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 55: Simulating Fog and Edge Computing
           Scenarios: An Overview and Research Challenges

    • Authors: Sergej Svorobej, Patricia Takako Endo, Malika Bendechache, Christos Filelis-Papadopoulos, Konstantinos M. Giannoutakis, George A. Gravvanis, Dimitrios Tzovaras, James Byrne, Theo Lynn
      First page: 55
      Abstract: The fourth industrial revolution heralds a paradigm shift in how people, processes, things, data and networks communicate and connect with each other. Conventional computing infrastructures are struggling to satisfy dramatic growth in demand from a deluge of connected heterogeneous end points located at the edge of networks while, at the same time, meeting quality of service levels. The complexity of computing at the edge makes it increasingly difficult for infrastructure providers to plan for and provision resources to meet this demand. While simulation frameworks are used extensively in the modelling of cloud computing environments in order to test and validate technical solutions, they are at a nascent stage of development and adoption for fog and edge computing. This paper provides an overview of challenges posed by fog and edge computing in relation to simulation.
      Citation: Future Internet
      PubDate: 2019-02-26
      DOI: 10.3390/fi11030055
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 56: On the Need for a General
           REST-Security Framework

    • Authors: Luigi Lo Iacono, Hoai Viet Nguyen, Peter Leo Gorski
      First page: 56
      Abstract: Contemporary software is inherently distributed. The principles guiding the design of such software have been mainly manifested by the service-oriented architecture (SOA) concept. In a SOA, applications are orchestrated by software services generally operated by distinct entities. Due to the latter fact, service security has been of importance in such systems ever since. A dominant protocol for implementing SOA-based systems is SOAP, which comes with a well-elaborated security framework. As an alternative to SOAP, the architectural style representational state transfer (REST) is gaining traction as a simple, lightweight and flexible guideline for designing distributed service systems that scale at large. This paper starts by introducing the basic constraints representing REST. Based on these foundations, the focus is afterwards drawn on the security needs of REST-based service systems. The limitations of transport-oriented protection means are emphasized and the demand for specific message-oriented safeguards is assessed. The paper then reviews the current activities in respect to REST-security and finds that the available schemes are mostly HTTP-centered and very heterogeneous. More importantly, all of the analyzed schemes contain vulnerabilities. The paper contributes a methodology on how to establish REST-security as a general security framework for protecting REST-based service systems of any kind by consistent and comprehensive protection means. First adoptions of the introduced approach are presented in relation to REST message authentication with instantiations for REST-ful HTTP (web/cloud services) and REST-ful constraint application protocol (CoAP) (internet of things (IoT) services).
      Citation: Future Internet
      PubDate: 2019-02-27
      DOI: 10.3390/fi11030056
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 57: Worldwide Connectivity for the
           Internet of Things Through LoRaWAN

    • Authors: Lorenzo Vangelista, Marco Centenaro
      First page: 57
      Abstract: The low-power wide-area network (LPWAN) paradigm is gradually gaining market acceptance. In particular, three prominent LPWAN technologies are emerging at the moment: LoRaWAN™ and SigFox™, which operate on unlicensed frequency bands, and NB-IoT, operating on licensed frequency bands. This paper deals with LoRaWAN™, and has the aim of describing a particularly interesting feature provided by the latest LoRaWAN™ specification—often neglected in the literature—i.e., the roaming capability between different operators of LoRaWAN™ networks, across the same country or even different countries. Recalling that LoRaWAN™ devices do not have a subscriber identification module (SIM) like cellular network terminals, at a first glance the implementation of roaming in LoRaWAN™ networks could seem intricate. The contribution of this paper consists in explaining the principles behind the implementation of a global LoRaWAN network, with particular focus on how to cope with the lack of the SIM in the architecture and how to realize roaming.
      Citation: Future Internet
      PubDate: 2019-03-02
      DOI: 10.3390/fi11030057
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 58: IoH: A Platform for the Intelligence
           of Home with a Context Awareness and Ambient Intelligence Approach

    • Authors: Luis Gomes, Carlos Ramos, Aria Jozi, Bruno Serra, Lucas Paiva, Zita Vale
      First page: 58
      Abstract: This paper presents IoH (Intelligence of Home), a platform developed to test some basic intelligent behaviors in Home context. Internet of Things, ambient intelligence and context awareness approaches motivated the development of IoH. The platform involves six layers, responsible by connectivity, persistency, unification, Internet of Things integration, subsystems integration and user interface. The integrated subsystems involve intelligent systems for light control, television brightness control, desk light control, persons counting and air conditioner control. The IoH platform is then tested for a real building, and results and conclusions are obtained. Different intelligent methods and technologies are used, form the use of a diversity of sensors, actuators, and controllers and processing units to a set of artificial intelligence approaches varying from machine learning and optimization algorithms to the use of sensor fusion and computer vision. The use of IoH day-by-day demonstrated an intelligent performance for the real building occupants.
      Citation: Future Internet
      PubDate: 2019-03-02
      DOI: 10.3390/fi11030058
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 59: myDIG: Personalized Illicit
           Domain-Specific Knowledge Discovery with No Programming

    • Authors: Mayank Kejriwal, Pedro Szekely
      First page: 59
      Abstract: With advances in machine learning, knowledge discovery systems have become very complicated to set up, requiring extensive tuning and programming effort. Democratizing such technology so that non-technical domain experts can avail themselves of these advances in an interactive and personalized way is an important problem. We describe myDIG, a highly modular, open source pipeline-construction system that is specifically geared towards investigative users (e.g., law enforcement) with no programming abilities. The myDIG system allows users both to build a knowledge graph of entities, relationships, and attributes for illicit domains from a raw HTML corpus and also to set up a personalized search interface for analyzing the structured knowledge. We use qualitative and quantitative data from five case studies involving investigative experts from illicit domains such as securities fraud and illegal firearms sales to illustrate the potential of myDIG.
      Citation: Future Internet
      PubDate: 2019-03-04
      DOI: 10.3390/fi11030059
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 60: Hot Topic Community Discovery on Cross
           Social Networks

    • Authors: Xuan Wang, Bofeng Zhang, Furong Chang
      First page: 60
      Abstract: The rapid development of online social networks has allowed users to obtain information, communicate with each other and express different opinions. Generally, in the same social network, users tend to be influenced by each other and have similar views. However, on another social network, users may have opposite views on the same event. Therefore, research undertaken on a single social network is unable to meet the needs of research on hot topic community discovery. “Cross social network” refers to multiple social networks. The integration of information from multiple social network platforms forms a new unified dataset. In the dataset, information from different platforms for the same event may contain similar or unique topics. This paper proposes a hot topic discovery method on cross social networks. Firstly, text data from different social networks are fused to build a unified model. Then, we obtain latent topic distributions from the unified model using the Labeled Biterm Latent Dirichlet Allocation (LB-LDA) model. Based on the distributions, similar topics are clustered to form several topic communities. Finally, we choose hot topic communities based on their scores. Experiment result on data from three social networks prove that our model is effective and has certain application value.
      Citation: Future Internet
      PubDate: 2019-03-04
      DOI: 10.3390/fi11030060
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 61: A Dual Attack Detection Technique to
           Identify Black and Gray Hole Attacks Using an Intrusion Detection System
           and a Connected Dominating Set in MANETs

    • Authors: Zulfiqar Ali Zardari, Jingsha He, Nafei Zhu, Khalid Hussain Mohammadani, Muhammad Salman Pathan, Muhammad Iftikhar Hussain, Muhammad Qasim Memon
      First page: 61
      Abstract: A mobile ad-hoc network (MANET) is a temporary network of wireless mobile nodes. In a MANET, it is assumed that all of the nodes cooperate with each other to transfer data packets in a multi-hop fashion. However, some malicious nodes don’t cooperate with other nodes and disturb the network through false routing information. In this paper, we propose a prominent technique, called dual attack detection for black and gray hole attacks (DDBG), for MANETs. The proposed DDBG technique selects the intrusion detection system (IDS) node using the connected dominating set (CDS) technique with two additional features; the energy and its nonexistence in the blacklist are also checked before putting the nodes into the IDS set. The CDS is an effective, distinguished, and localized approach for detecting nearly-connected dominating sets of nodes in a small range in mobile ad hoc networks. The selected IDS nodes broadcast a kind of status packet within a size of the dominating set for retrieving the complete behavioral information from their nodes. Later, IDS nodes use our DDBG technique to analyze the collected behavioral information to detect the malicious nodes and add them to the blacklist if the behavior of the node is suspicious. Our experimental results show that the quality of the service parameters of the proposed technique outperforms the existing routing schemes.
      Citation: Future Internet
      PubDate: 2019-03-05
      DOI: 10.3390/fi11030061
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 62: Modeling of Information Operations
           Effects: Technological Systems Example

    • Authors: Alexander Geyda, Igor Lysenko
      First page: 62
      Abstract: The article outlines conceptual and corresponding formal models of system functioning. Models provide means for estimation of information operation effects and the operational properties of systems and their functioning. Such systems are changed due to information operations. Examples of operational properties are efficiency, the effectiveness of system functioning, system capabilities and system potential. Operational properties are estimated based on functioning effects. Such effects of information operations are manifested through a system functioning under the conditions of a changing environment. An estimation of effects and operational properties is fulfilled analytically. It is made through plotting the dependences of the predicted values of effects and operational properties of information operations and corresponding IT usage against the variables and options of problems solved. To develop this type of model, the use of information operations during system functioning is analyzed through an example of a technological system. General concepts and principles of the modeling of information operations during the operation of such systems are defined. An exemplary modeling of the effects of technological information, and the related technological non-information operations of technological systems operation is provided. Based on concept models of information operations of technological systems, functioning set-theoretical models followed by functional models are introduced. An example of operational properties indicators estimation is considered. It is based on Architecture of Integrated Information Systems (ARIS) diagramming tools’ usage. Use cases of such indicators include choosing optimal information operations characteristics.
      Citation: Future Internet
      PubDate: 2019-03-05
      DOI: 10.3390/fi11030062
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 63: Cyber Security Threat Modeling for
           Supply Chain Organizational Environments

    • Authors: Abel Yeboah-Ofori, Shareeful Islam
      First page: 63
      Abstract: Cyber security in a supply chain (SC) provides an organization the secure network facilities to meet its overall business objectives. The integration of technologies has improved business processes, increased production speed, and reduced distribution costs. However, the increased interdependencies among various supply chain stakeholders have brought many challenges including lack of third party audit mechanisms and cascading cyber threats. This has led to attacks such as the manipulation of the design specifications, alterations, and manipulation during distribution. The aim of this paper is to investigate and understand supply chain threats. In particular, the paper contributes towards modeling and analyzing CSC attacks and cyber threat reporting among supply chain stakeholders. We consider concepts such as goal, actor, attack, TTP, and threat actor relevant to the supply chain, threat model, and requirements domain, and modeled the attack using the widely known STIX threat model. The proposed model was analyzed using a running example of a smart grid case study and an algorithm to model the attack. A discrete probability method for calculating the conditional probabilities was used to determine the attack propagation and cascading effects, and the results showed that our approach effectively analyzed the threats. We have recommended a list of CSC controls to improve the overall security of the studied organization.
      Citation: Future Internet
      PubDate: 2019-03-05
      DOI: 10.3390/fi11030063
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 64: A Cache Placement Strategy with Energy
           Consumption Optimization in Information-Centric Networking

    • Authors: Xin Zheng, Gaocai Wang, Qifei Zhao
      First page: 64
      Abstract: With the rapid development of cloud computing, big data, and Internet of Things, Information-Centric Networking (ICN) has become a novel hotspot in the field of future Internet architecture, and new problems have appeared. In particular, more researchers consider information naming, delivery, mobility, and security in ICN. In this paper, we mainly focus on the cache placement strategy and network performance of ICN, and propose a cache placement strategy with energy consumption optimization. In order to optimize the energy consumption of the ICN, the best cache placement node is selected from the view of users. First of all, the distance sequence of different nodes arriving at each user is obtained in terms of detection results of network distribution channels, and the corresponding energy consumption of information distribution is obtained from the distance sequence. Secondly, the reward function of the cache node is derived using two factors of energy consumption, which includes the additional energy consumed by the change of the cache node and the energy consumption of the content distribution. Finally, we construct the optimal stopping theory problem to solve the maximum expected energy saving. In simulations, we give the comparison results of energy savings, caching benefit, and delivery success rate. The results show that the strategy proposed by this paper has higher delivery success rate and lower energy consumption than other strategies.
      Citation: Future Internet
      PubDate: 2019-03-05
      DOI: 10.3390/fi11030064
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 65: A Game-Theoretic Analysis for
           Distributed Honeypots

    • Authors: Yang Li, Leyi Shi, Haijie Feng
      First page: 65
      Abstract: A honeypot is a decoy tool for luring an attacker and interacting with it, further consuming its resources. Due to its fake property, a honeypot can be recognized by the adversary and loses its value. Honeypots equipped with dynamic characteristics are capable of deceiving intruders. However, most of their dynamic properties are reflected in the system configuration, rather than the location. Dynamic honeypots are faced with the risk of being identified and avoided. In this paper, we focus on the dynamic locations of honeypots and propose a distributed honeypot scheme. By periodically changing the services, the attacker cannot distinguish the real services from honeypots, and the illegal attack flow can be recognized. We adopt game theory to illustrate the effectiveness of our system. Gambit simulations are conducted to validate our proposed scheme. The game-theoretic reasoning shows that our system comprises an innovative system defense. Further simulation results prove that the proposed scheme improves the server’s payoff and that the attacker tends to abandon launching attacks. Therefore, the proposed distributed honeypot scheme is effective for network security.
      Citation: Future Internet
      PubDate: 2019-03-05
      DOI: 10.3390/fi11030065
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 66: Communication Protocols of an
           Industrial Internet of Things Environment: A Comparative Study

    • Authors: Samer Jaloudi
      First page: 66
      Abstract: Most industrial and SCADA-like (supervisory control and data acquisition) systems use proprietary communication protocols, and hence interoperability is not fulfilled. However, the MODBUS TCP is an open de facto standard, and is used for some automation and telecontrol systems. It is based on a polling mechanism and follows the synchronous request–response pattern, as opposed to the asynchronous publish–subscribe pattern. In this study, polling-based and event-based protocols are investigated to realize an open and interoperable Industrial Internet of Things (IIoT) environment. Many Internet of Things (IoT) protocols are introduced and compared, and the message queuing telemetry transport (MQTT) is chosen as the event-based, publish–subscribe protocol. The study shows that MODBUS defines an optimized message structure in the application layer, which is dedicated to industrial applications. In addition, it shows that an event-oriented IoT protocol complements the MODBUS TCP but cannot replace it. Therefore, two scenarios are proposed to build the IIoT environment. The first scenario is to consider the MODBUS TCP as an IoT protocol, and build the environment using the MODBUS TCP on a standalone basis. The second scenario is to use MQTT in conjunction with the MODBUS TCP. The first scenario is efficient and complies with most industrial applications where the request–response pattern is needed only. If the publish–subscribe pattern is needed, the MQTT in the second scenario complements the MODBUS TCP and eliminates the need for a gateway; however, MQTT lacks interoperability. To maintain a homogeneous message structure for the entire environment, industrial data are organized using the structure of MODBUS messages, formatted in the UTF-8, and then transferred in the payload of an MQTT publish message. The open and interoperable environment can be used for Internet SCADA, Internet-based monitoring, and industrial control systems.
      Citation: Future Internet
      PubDate: 2019-03-07
      DOI: 10.3390/fi11030066
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 67: Gamification vs. Privacy: Identifying
           and Analysing the Major Concerns

    • Authors: Aikaterini-Georgia Mavroeidi, Angeliki Kitsiou, Christos Kalloniatis, Stefanos Gritzalis
      First page: 67
      Abstract: Gamification, the use of game design elements in applications that are not games, has been developed to provide attractive environments and maintain user interest in several domains. In domains such as education, marketing and health, where gamification techniques are applied, user engagement in applications has increased. In these applications the protection of users’ privacy is an important aspect to consider, due to the applications obtaining a record of the personal information of their users. Thus, the purpose of this paper is to identify if applications where gamification is applied do respect users’ privacy. For the accomplishment of this aim, two main steps have been implemented. Since the main principle of gamification is the existence of game elements, the first step was to identify the set of game elements recorded in the literature that are commonly applied in various applications. Afterwards, an examination of the relationship between these elements and privacy requirements was implemented in order to identify which elements conflict with the privacy requirements leading to potential privacy violations and which elements do not. Α conceptual model according to the results of this examination was designed, which presents how elements conflict with requirements. Based on the results, there are indeed game elements which can lead to privacy violations. The results of this work provide valuable guidance to software developers, especially during the design stages of gamified applications since it helps them to consider the protection of users’ privacy in parallel from the early stages of the application development onwards.
      Citation: Future Internet
      PubDate: 2019-03-07
      DOI: 10.3390/fi11030067
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 68: Snack Texture Estimation System Using
           a Simple Equipment and Neural Network Model

    • Authors: Shigeru Kato, Naoki Wada, Ryuji Ito, Takaya Shiozaki, Yudai Nishiyama, Tomomichi Kagawa
      First page: 68
      Abstract: Texture evaluation is manually performed in general, and such analytical tasks can get cumbersome. In this regard, a neural network model is employed in this study. This paper describes a system that can estimate the food texture of snacks. The system comprises a simple equipment unit and an artificial neural network model. The equipment simultaneously examines the load and sound when a snack is pressed. The neural network model analyzes the load change and sound signals and then outputs a numerical value within the range (0,1) to express the level of textures such as “crunchiness” and “crispness”. Experimental results validate the model’s capacity to output moderate texture values of the snacks. In addition, we applied the convolutional neural network (CNN) model to classify snacks and the capability of the CNN model for texture estimation is discussed.
      Citation: Future Internet
      PubDate: 2019-03-08
      DOI: 10.3390/fi11030068
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 69: VNF Placement Optimization at the Edge
           and Cloud †

    • Authors: Aris Leivadeas, George Kesidis, Mohamed Ibnkahla, Ioannis Lambadaris
      First page: 69
      Abstract: Network Function Virtualization (NFV) has revolutionized the way network services are offered to end users. Individual network functions are decoupled from expensive and dedicated middleboxes and are now provided as software-based virtualized entities called Virtualized Network Functions (VNFs). NFV is often complemented with the Cloud Computing paradigm to provide networking functions to enterprise customers and end-users remote from their premises. NFV along with Cloud Computing has also started to be seen in Internet of Things (IoT) platforms as a means to provide networking functions to the IoT traffic. The intermix of IoT, NFV, and Cloud technologies, however, is still in its infancy creating a rich and open future research area. To this end, in this paper, we propose a novel approach to facilitate the placement and deployment of service chained VNFs in a network cloud infrastructure that can be extended using the Mobile Edge Computing (MEC) infrastructure for accommodating mission critical and delay sensitive traffic. Our aim is to minimize the end-to-end communication delay while keeping the overall deployment cost to minimum. Results reveal that the proposed approach can significantly reduce the delay experienced, while satisfying the Service Providers’ goal of low deployment costs.
      Citation: Future Internet
      PubDate: 2019-03-09
      DOI: 10.3390/fi11030069
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 70: Software-Defined Heterogeneous
           Vehicular Networking: The Architectural Design and Open Challenges

    • Authors: Adnan Mahmood, Wei Emma Zhang, Quan Z. Sheng
      First page: 70
      Abstract: The promising advancements in the telecommunications and automotive sectors over the years have empowered drivers with highly innovative communication and sensing capabilities, in turn paving the way for the next-generation connected and autonomous vehicles. Today, vehicles communicate wirelessly with other vehicles and vulnerable pedestrians in their immediate vicinity to share timely safety-critical information primarily for collision mitigation. Furthermore, vehicles connect with the traffic management entities via their supporting network infrastructure to become more aware of any potential hazards on the roads and for guidance pertinent to their current and anticipated speeds and travelling course to ensure more efficient traffic flows. Therefore, a secure and low-latency communication is highly indispensable in order to meet the stringent performance requirements of such safety-critical vehicular applications. However, the heterogeneity of diverse radio access technologies and inflexibility in their deployment results in network fragmentation and inefficient resource utilization, and these, therefore, act as bottlenecks in realizing the aims for a highly efficient vehicular networking architecture. In order to overcome such sorts of bottlenecks, this article brings forth the current state-of-the-art in the context of intelligent transportation systems (ITS) and subsequently proposes a software-defined heterogeneous vehicular networking (SDHVNet) architecture for ensuring a highly agile networking infrastructure to ensure rapid network innovation on-demand. Finally, a number of potential architectural challenges and their probable solutions are discussed.
      Citation: Future Internet
      PubDate: 2019-03-11
      DOI: 10.3390/fi11030070
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 71: Effectiveness of Segment Routing
           Technology in Reducing the Bandwidth and Cloud Resources Provisioning
           Times in Network Function Virtualization Architectures

    • Authors: Vincenzo Eramo, Francesco G. Lavacca, Tiziana Catena, Marco Polverini, Antonio Cianfrani
      First page: 71
      Abstract: Network Function Virtualization is a new technology allowing for a elastic cloud and bandwidth resource allocation. The technology requires an orchestrator whose role is the service and resource orchestration. It receives service requests, each one characterized by a Service Function Chain, which is a set of service functions to be executed according to a given order. It implements an algorithm for deciding where both to allocate the cloud and bandwidth resources and to route the SFCs. In a traditional orchestration algorithm, the orchestrator has a detailed knowledge of the cloud and network infrastructures and that can lead to high computational complexity of the SFC Routing and Cloud and Bandwidth resource Allocation (SRCBA) algorithm. In this paper, we propose and evaluate the effectiveness of a scalable orchestration architecture inherited by the one proposed within the European Telecommunications Standards Institute (ETSI) and based on the functional separation of an NFV orchestrator in Resource Orchestrator (RO) and Network Service Orchestrator (NSO). Each cloud domain is equipped with an RO whose task is to provide a simple and abstract representation of the cloud infrastructure. These representations are notified of the NSO that can apply a simplified and less complex SRCBA algorithm. In addition, we show how the segment routing technology can help to simplify the SFC routing by means of an effective addressing of the service functions. The scalable orchestration solution has been investigated and compared to the one of a traditional orchestrator in some network scenarios and varying the number of cloud domains. We have verified that the execution time of the SRCBA algorithm can be drastically reduced without degrading the performance in terms of cloud and bandwidth resource costs.
      Citation: Future Internet
      PubDate: 2019-03-12
      DOI: 10.3390/fi11030071
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 72: Environmental Hazards: A Coverage
           Response Approach

    • Authors: Paul J. Croft
      First page: 72
      Abstract: The rapid rise and implementation of Smart Systems (i.e., multi-functional observation and platform systems that depict settings and/or identify situations or features of interest, often in real-time) has inversely paralleled and readily exposed the reduced capacity of human and societal systems to effectively respond to environmental hazards. This overarching review and essay explores the complex set of interactions found among Smart, Societal, and Environmental Systems. The resulting rise in the poorly performing response solutions to environmental hazards that has occurred despite best practices, detailed forecast information, and the use and application of real-time in situ observational platforms are considered. The application of Smart Systems, relevant architectures, and ever-increasing numbers of applications and tools development by individuals as they interact with Smart Systems offers a means to ameliorate and resolve confounding found among all of the interdependent Systems. The interactions of human systems with environmental hazards further expose society’s complex operational vulnerabilities and gaps in response to such threats. An examination of decision-making, the auto-reactive nature of responses before, during, and after environmental hazards; and the lack of scalability and comparability are presented with regard to the prospects of applying probabilistic methods, cross-scale time and space domains; anticipated impacts, and the need to account for multimodal actions and reactions—including psycho-social contributions. Assimilation of these concepts and principles in Smart System architectures, applications, and tools is essential to ensure future viability and functionalities with regard to environmental hazards and to produce an effective set of societal engagement responses. Achieving the promise of Smart Systems relative to environmental hazards will require an extensive transdisciplinary approach to tie psycho-social behaviors directly with non-human components and systems in order to close actionable gaps in response. Pathways to achieve a more comprehensive understanding are given for consideration by the wide diversity of disciplines necessary to move forward in Smart Systems as tied with the societal response to environmental hazards.
      Citation: Future Internet
      PubDate: 2019-03-14
      DOI: 10.3390/fi11030072
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 73: Reviewing Cyber Security Social

    • Authors: Hussain Aldawood, Geoffrey Skinner
      First page: 73
      Abstract: The idea and perception of good cyber security protection remains at the forefront of many organizations’ information and communication technology strategy and investment. However, delving deeper into the details of its implementation reveals that organizations’ human capital cyber security knowledge bases are very low. In particular, the lack of social engineering awareness is a concern in the context of human cyber security risks. This study highlights pitfalls and ongoing issues that organizations encounter in the process of developing the human knowledge to protect from social engineering attacks. A detailed literature review is provided to support these arguments with analysis of contemporary approaches. The findings show that despite state-of-the-art cyber security preparations and trained personnel, hackers are still successful in their malicious acts of stealing sensitive information that is crucial to organizations. The factors influencing users’ proficiency in threat detection and mitigation have been identified as business environmental, social, political, constitutional, organizational, economical, and personal. Challenges with respect to both traditional and modern tools have been analyzed to suggest the need for profiling at-risk employees (including new hires) and developing training programs at each level of the hierarchy to ensure that the hackers do not succeed.
      Citation: Future Internet
      PubDate: 2019-03-18
      DOI: 10.3390/fi11030073
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 74: An Overview on Push-Based
           Communication Models for Information-Centric Networking

    • Authors: Rute C. Sofia, Paulo M. Mendes
      First page: 74
      Abstract: Information-centric networking integrates by design a pull-based model which brings in advantages in terms of control as well as of in-network caching strategies. Currently, ICN main areas of action concern content distribution and IoT, both of which are environments that often require support for periodic and even-triggered data transmission. Such environments can benefit from push-based communication to achieve faster data forwarding. This paper provides an overview on the current push-based mechanisms that can be applied to information-centric paradigms, explaining the trade-off associated with the different approaches. Moreover, the paper provides design guidelines for integrating push communications in information-centric networking, having as example the application of this networking architecture in IoT environments.
      Citation: Future Internet
      PubDate: 2019-03-21
      DOI: 10.3390/fi11030074
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 75: Dynamic SDN Controller Load Balancing

    • Authors: Hadar Sufiev, Yoram Haddad, Leonid Barenboim, José Soler
      First page: 75
      Abstract: The software defined networking (SDN) paradigm separates the control plane from the data plane, where an SDN controller receives requests from its connected switches and manages the operation of the switches under its control. Reassignments between switches and their controllers are performed dynamically, in order to balance the load over SDN controllers. In order to perform load balancing, most dynamic assignment solutions use a central element to gather information requests for reassignment of switches. Increasing the number of controllers causes a scalability problem, when one super controller is used for all controllers and gathers information from all switches. In a large network, the distances between the controllers is sometimes a constraint for assigning them switches. In this paper, a new approach is presented to solve the well-known load balancing problem in the SDN control plane. This approach implies less load on the central element and meeting the maximum distance constraint allowed between controllers. An architecture with two levels of load balancing is defined. At the top level, the main component called Super Controller, arranges the controllers in clusters, so that there is a balance between the loads of the clusters. At the bottom level, in each cluster there is a dedicated controller called Master Controller, which performs a reassignment of the switches in order to balance the loads between the controllers. We provide a two-phase algorithm, called Dynamic Controllers Clustering algorithm, for the top level of load balancing operation. The load balancing operation takes place at regular intervals. The length of the cycle in which the operation is performed can be shorter, since the top-level operation can run independently of the bottom level operation. Shortening cycle time allows for more accurate results of load balancing. Theoretical analysis demonstrates that our algorithm provides a near-optimal solution. Simulation results show that our dynamic clustering improves fixed clustering by a multiplicative factor of 5.
      Citation: Future Internet
      PubDate: 2019-03-21
      DOI: 10.3390/fi11030075
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 76: eHealth Integrity Model Based on
           Permissioned Blockchain

    • Authors: Tomasz Hyla, Jerzy Pejaś
      First page: 76
      Abstract: (1) Background: Large eHealth systems should have a mechanism to detect unauthorized changes in patients’ medical documentation, access permissions, and logs. This is due to the fact that modern eHealth systems are connected with many healthcare providers and sites. (2) Methods: Design-science methodology was used to create an integrity-protection service model based on blockchain technology. Based on the problem of transactional transparency, requirements were specified and a model was designed. After that, the model’s security and performance were evaluated. (3) Results: a blockchain-based eHealth integrity model for ensuring information integrity in eHealth systems that uses a permissioned blockchain with off-chain information storage was created. In contrast to existing solutions, the proposed model allows information removal, which in many countries’ eHealth systems is a legal requirement, and is based on a blockchain using the Practical Byzantine Fault Tolerant algorithm. (4) Conclusion: A blockchain can be used to store medical data or only security-related data. In the proposed model, a blockchain is mainly used to implement a data-integrity service. This service can be implemented using other mechanisms, but a blockchain provides a solution that does not require trusted third parties, works in a distributed eHealth environment, and supports document removal.
      Citation: Future Internet
      PubDate: 2019-03-24
      DOI: 10.3390/fi11030076
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 77: Open Data for Open Innovation: An
           Analysis of Literature Characteristics

    • Authors: Diego Corrales-Garay, Eva-María Mora-Valentín, Marta Ortiz-de-Urbina-Criado
      First page: 77
      Abstract: In this paper, we review some characteristics of the literature that studies the uses and applications of open data for open innovation. Three research questions are proposed about both topics: (1) What journals, conferences and authors have published papers about the use of open data for open innovation' (2) What knowledge areas have been analysed in research on open data for open innovation' and (3) What are the methodological characteristics of the papers on open data for open innovation' To answer the first question, we use a descriptive analysis to identify the relevant journals and authors. To address the second question, we identify the knowledge areas of the studies about open data for open innovation. Finally, we analyse the methodological characteristics of the literature (type of study, analytical techniques, sources of information and geographical area). Our results show that the applications of open data for open innovation are interesting but their multidisciplinary nature makes the context complex and diverse, opening up many future avenues for research. To develop a future research agenda, we propose a theoretical model and some research questions to analyse the open data impact process for open innovation.
      Citation: Future Internet
      PubDate: 2019-03-24
      DOI: 10.3390/fi11030077
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 78: Environmental-Based Speed
           Recommendation for Future Smart Cars

    • Authors: Ioannis Galanis, Iraklis Anagnostopoulos, Priyaa Gurunathan, Dona Burkard
      First page: 78
      Abstract: Modern vehicles are enhanced with increased computation, communication and sensing capabilities, providing a variety of new features that pave the way for the deployment of more sophisticated services. Specifically, smart cars employ hundreds of sensors and electronic systems in order to obtain situational and environmental information. This rapid growth of on-vehicle multi-sensor inputs along with off-vehicle data streams introduce the smart car era. Thus, systematic techniques for combining information provided by on- and off-vehicle car connectivity are of remarkable importance for the availability and robustness of the overall system. This paper presents a new method to employ service oriented agents that cohesively align on- and off-vehicle information in order to estimate the current status of the car. In particular, this work combines, integrates, and evaluates multiple information sources targeting future smart cars. Specifically, the proposed methodology leverages weather-based, on-route, and on-vehicle information. As a use case, the presented work informs the driver about the recommended speed that the car should adapt to, based on the current status of the car. It also validates the proposed speed with real-time vehicular measurements.
      Citation: Future Internet
      PubDate: 2019-03-24
      DOI: 10.3390/fi11030078
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 79: Topic-Specific Emotion Mining Model
           for Online Comments

    • Authors: Luo, Yi
      First page: 79
      Abstract: Nowadays, massive texts are generated on the web, which contain a variety of viewpoints, attitudes, and emotions for products and services. Subjective information mining of online comments is vital for enterprises to improve their products or services and for consumers to make purchase decisions. Various effective methods, the mainstream one of which is the topic model, have been put forward to solve this problem. Although most of topic models can mine the topic-level emotion of the product comments, they do not consider interword relations and the number of topics determined adaptively, which leads to poor comprehensibility, high time requirement, and low accuracy. To solve the above problems, this paper proposes an unsupervised Topic-Specific Emotion Mining Model (TSEM), which adds corresponding relationship between aspect words and opinion words to express comments as a bag of aspect–opinion pairs. On one hand, the rich semantic information obtained by adding interword relationship can enhance the comprehensibility of results. On the other hand, text dimensions reduced by adding relationships can cut the computation time. In addition, the number of topics in our model is adaptively determined by calculating perplexity to improve the emotion accuracy of the topic level. Our experiments using Taobao commodity comments achieve better results than baseline models in terms of accuracy, computation time, and comprehensibility. Therefore, our proposed model can be effectively applied to online comment emotion mining tasks.
      Citation: Future Internet
      PubDate: 2019-03-24
      DOI: 10.3390/fi11030079
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 80: Experimental Study on the Utility and
           Future of Collaborative Consumption Platforms Offering Tourism Related

    • Authors: Joan-Francesc Fondevila-Gascón, Gaspar Berbel, Mònica Muñoz-González
      First page: 80
      Abstract: The present study analyzes four well-known online platforms used in the tourist industry for travelling, accommodation, eating, and touring (Blablacar, Airbnb, Eatwith, and Trip4real). The objective is to analyze the utility of the portals, intentions for future use and recommendation (prospective), and reputation. The method is an experimental design with a control group and experimental group. Within both groups, three scales were applied. The results indicate clear differences between the control and experimental groups, valuing above all the utility and the intent to use again when the group is exposed to the portals from a needs-based situation (experimental group). The analysis demonstrates a factorial structure that validates the model. At the same time, the results indicate a greater interest in using Trip4Real over BlaBlaCar. Generation Z, the youngest generation, shows greater confidence in the services and greater interest in using tourism related collaborative consumption platforms in the future.
      Citation: Future Internet
      PubDate: 2019-03-25
      DOI: 10.3390/fi11030080
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 81: Nonlinear Analysis of Built-in Sensor
           in Smart Device under the Condition of Voice Actuating

    • Authors: Ning Zhao, Yuhe Liu, Junjie Shen
      First page: 81
      Abstract: A built-in sensor in a smart device, such as the accelerometer and the gyroscope, will produce an obvious nonlinear output when it receives voice signal. In this paper, based on the chaotic theory, the nonlinearity of smartphone built-in accelerometer is revealed by phase space reconstructing after we calculate several nonlinearity characteristics, such as best delay time, embedding dimension, and the attractor of accelerometer system, under the condition of voice commands inputting. The results of theoretical calculation and experiments show that this specific nonlinearity could lay a foundation for further signal extraction and analysis.
      Citation: Future Internet
      PubDate: 2019-03-26
      DOI: 10.3390/fi11030081
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 82: An Access Control Model for Preventing
           Virtual Machine Hopping Attack

    • Authors: Ying Dong, Zhou Lei
      First page: 82
      Abstract: As a new type of service computing model, cloud computing provides various services through the Internet. Virtual machine (VM) hopping is a security issue often encountered in the virtualization layer. Once it occurs, it directly affects the reliability of the entire computing platform. Therefore, we have thoroughly studied the virtual machine hopping attack. In addition, we designed the access control model PVMH (Prevent VM hopping) to prevent VM hopping attacks based on the BLP model and the Biba model. Finally, we implemented the model on the Xen platform. The experiments demonstrate that our PVMH module succeeds in preventing VM hopping attack with acceptable loss to virtual machine performance.
      Citation: Future Internet
      PubDate: 2019-03-26
      DOI: 10.3390/fi11030082
      Issue No: Vol. 11, No. 3 (2019)
  • Future Internet, Vol. 11, Pages 26: A Spatial Prediction-Based
           Motion-Compensated Frame Rate Up-Conversion

    • Authors: Yanli Li, Wendan Ma, Yue Han
      First page: 26
      Abstract: In Multimedia Internet of Things (IoT), in order to reduce the bandwidth consumption of wireless channels, Motion-Compensated Frame Rate Up-Conversion (MC-FRUC) is often used to support the low-bitrate video communication. In this paper, we propose a spatial predictive algorithm which is used to improve the performance of MC-FRUC. The core of the proposed algorithm is a predictive model to split a frame into two kinds of blocks: basic blocks and absent blocks. Then an improved bilateral motion estimation is proposed to compute the Motion Vectors (MVs) of basic blocks. Finally, with the spatial correlation of Motion Vector Field (MVF), the MV of an absent block is predicted based on the MVs of its neighboring basic blocks. Experimental results show that the proposed spatial prediction algorithm can improve both the objective and the subjective quality of the interpolated frame, with a low computational complexity.
      Citation: Future Internet
      PubDate: 2019-01-23
      DOI: 10.3390/fi11020026
      Issue No: Vol. 11, No. 2 (2019)
  • Future Internet, Vol. 11, Pages 27: An Overview of Vehicular

    • Authors: Fabio Arena, Giovanni Pau
      First page: 27
      Abstract: The transport sector is commonly subordinate to several issues, such as traffic congestion and accidents. Despite this, in recent years, it is also evolving with regard to cooperation between vehicles. The fundamental objective of this trend is to increase road safety, attempting to anticipate the circumstances of potential danger. Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I) and Vehicle-to-Everything (V2X) technologies strive to give communication models that can be employed by vehicles in different application contexts. The resulting infrastructure is an ad-hoc mesh network whose nodes are not only vehicles but also all mobile devices equipped with wireless modules. The interaction between the multiple connected entities consists of information exchange through the adoption of suitable communication protocols. The main aim of the review carried out in this paper is to examine and assess the most relevant systems, applications, and communication protocols that will distinguish the future road infrastructures used by vehicles. The results of the investigation reveal the real benefits that technological cooperation can involve in road safety.
      Citation: Future Internet
      PubDate: 2019-01-24
      DOI: 10.3390/fi11020027
      Issue No: Vol. 11, No. 2 (2019)
  • Future Internet, Vol. 11, Pages 28: T-Move: A Light-Weight Protocol for
           Improved QoS in Content-Centric Networks with Producer Mobility

    • Authors: Swaroopa Korla, Shanti Chilukuri
      First page: 28
      Abstract: Recent interest in applications where content is of primary interest has triggered the exploration of a variety of protocols and algorithms. For such networks that are information-centric, architectures such as the Content-Centric Networking have been proven to result in good network performance. However, such architectures are still evolving to cater for application-specific requirements. This paper proposes T-Move, a light-weight solution for producer mobility and caching at the edge that is especially suitable for content-centric networks with mobile content producers. T-Move introduces a novel concept called trendiness of data for Content-Centric Networking (CCN)/Named Data Networking (NDN)-based networks. It enhances network performance and quality of service (QoS) using two strategies—cache replacement and proactive content-pushing for handling producer mobility—both based on trendiness. It uses simple operations and smaller control message overhead and is suitable for networks where the response needs to be quick. Simulation results using ndnSIM show reduced traffic, content retrieval time, and increased cache hit ratio with T-Move, when compared to MAP-Me and plain NDN for networks of different sizes and mobility rates.
      Citation: Future Internet
      PubDate: 2019-01-27
      DOI: 10.3390/fi11020028
      Issue No: Vol. 11, No. 2 (2019)
  • Future Internet, Vol. 11, Pages 29: My Smartphone tattles: Considering
           Popularity of Messages in Opportunistic Data Dissemination

    • Authors: Asanga Udugama, Jens Dede, Anna Förster, Vishnupriya Kuppusamy, Koojana Kuladinithi, Andreas Timm-Giel, Zeynep Vatandas
      First page: 29
      Abstract: Opportunistic networks have recently seen increasing interest in the networking community. They can serve a range of application scenarios, most of them being destination-less, i.e., without a-priori knowledge of who is the final destination of a message. In this paper, we explore the usage of data popularity for improving the efficiency of data forwarding in opportunistic networks. Whether a message will become popular or not is not known before disseminating it to users. Thus, popularity needs to be estimated in a distributed manner considering a local context. We propose Keetchi, a data forwarding protocol based on Q-Learning to give more preference to popular data rather than less popular data. Our extensive simulation comparison between Keetchi and the well known Epidemic protocol shows that the network overhead of data forwarding can be significantly reduced while keeping the delivery rate the same.
      Citation: Future Internet
      PubDate: 2019-01-29
      DOI: 10.3390/fi11020029
      Issue No: Vol. 11, No. 2 (2019)
  • Future Internet, Vol. 11, Pages 30: An Investigation into Healthcare-Data

    • Authors: Aaron Boddy, William Hurst, Michael Mackay, Abdennour El Rhalibi, Thar Baker, Casimiro A. Curbelo Montañez
      First page: 30
      Abstract: Visualising complex data facilitates a more comprehensive stage for conveying knowledge. Within the medical data domain, there is an increasing requirement for valuable and accurate information. Patients need to be confident that their data is being stored safely and securely. As such, it is now becoming necessary to visualise data patterns and trends in real-time to identify erratic and anomalous network access behaviours. In this paper, an investigation into modelling data flow within healthcare infrastructures is presented; where a dataset from a Liverpool-based (UK) hospital is employed for the case study. Specifically, a visualisation of transmission control protocol (TCP) socket connections is put forward, as an investigation into the data complexity and user interaction events within healthcare networks. In addition, a filtering algorithm is proposed for noise reduction in the TCP dataset. Positive results from using this algorithm are apparent on visual inspection, where noise is reduced by up to 89.84%.
      Citation: Future Internet
      PubDate: 2019-01-30
      DOI: 10.3390/fi11020030
      Issue No: Vol. 11, No. 2 (2019)
  • Future Internet, Vol. 11, Pages 31: Dual-Band Monopole Antenna for RFID

    • Authors: Naser Ojaroudi Parchin, Haleh Jahanbakhsh Basherlou, Raed A. Abd-Alhameed, James M. Noras
      First page: 31
      Abstract: Over the past decade, radio-frequency identification (RFID) technology has attracted significant attention and become very popular in different applications, such as identification, management, and monitoring. In this study, a dual-band microstrip-fed monopole antenna has been introduced for RFID applications. The antenna is designed to work at the frequency ranges of 2.2–2.6 GHz and 5.3–6.8 GHz, covering 2.4/5.8 GHz RFID operation bands. The antenna structure is like a modified F-shaped radiator. It is printed on an FR-4 dielectric with an overall size of 38 × 45 × 1.6 mm3. Fundamental characteristics of the antenna in terms of return loss, Smith Chart, phase, radiation pattern, and antenna gain are investigated and good results are obtained. Simulations have been carried out using computer simulation technology (CST) software. A prototype of the antenna was fabricated and its characteristics were measured. The measured results show good agreement with simulations. The structure of the antenna is planar, simple to design and fabricate, easy to integrate with RF circuit, and suitable for use in RFID systems.
      Citation: Future Internet
      PubDate: 2019-01-30
      DOI: 10.3390/fi11020031
      Issue No: Vol. 11, No. 2 (2019)
  • Future Internet, Vol. 11, Pages 32: Important Factors for Improving Google
           Search Rank

    • Authors: Christos Ziakis, Maro Vlachopoulou, Theodosios Kyrkoudis, Makrina Karagkiozidou
      First page: 32
      Abstract: The World Wide Web has become an essential modern tool for people’s daily routine. The fact that it is a convenient means for communication and information search has made it extremely popular. This fact led companies to start using online advertising by creating corporate websites. With the rapid increase in the number of websites, search engines had to come up with a solution of algorithms and programs to qualify the results of a search and provide the users with relevant content to their search. On the other side, developers, in pursuit of the highest rankings in the search engine result pages (SERPs), began to study and observe how search engines work and which factors contribute to higher rankings. The knowledge that has been extracted constituted the base for the creation of the profession of Search Engine Optimization (SEO). This paper consists of two parts. The first part aims to perform a literature review of the factors that affect the ranking of websites in the SERPs and to highlight the top factors that contribute to better ranking. To achieve this goal, a collection and analysis of academic papers was conducted. According to our research, 24 website characteristics came up as factors affecting any website’s ranking, with the most references mentioning quality and quantity of backlinks, social media support, keyword in title tag, website structure, website size, loading time, domain age, and keyword density. The second part consists of our research which was conducted manually using the phrases “hotel Athens”, “email marketing”, and “casual shoes”. For each one of these keywords, the first 15 Google results were examined considering the factors found in the literature review. For the measurement of the significance of each factor, the Spearman correlation was calculated and every factor was compared with the ranking of the results individually. The findings of the research showed us that the top factors that contribute to higher rankings are the existence of website SSL certificate as well as keyword in URL, the quantity of backlinks pointing to a website, the text length, and the domain age, which is not perfectly aligned with what the literature review showed us.
      Citation: Future Internet
      PubDate: 2019-01-30
      DOI: 10.3390/fi11020032
      Issue No: Vol. 11, No. 2 (2019)
  • Future Internet, Vol. 11, Pages 33: Contribution of the Web of Things and
           of the Opportunistic Computing to the Smart Agriculture: A Practical

    • Authors: Lionel Touseau, Nicolas Sommer
      First page: 33
      Abstract: With the emergence of the Internet of Things, environmental sensing has been gaining interest, promising to improve agricultural practices by facilitating decision-making based on gathered environmental data (i.e., weather forecasting, crop monitoring, and soil moisture sensing). Environmental sensing, and by extension what is referred to as precision or smart agriculture, pose new challenges, especially regarding the collection of environmental data in the presence of connectivity disruptions, their gathering, and their exploitation by end-users or by systems that must perform actions according to the values of those collected data. In this paper, we present a middleware platform for the Internet of Things that implements disruption tolerant opportunistic networking and computing techniques, and that makes it possible to expose and manage physical objects through Web-based protocols, standards and technologies, thus providing interoperability between objects and creating a Web of Things (WoT). This WoT-based opportunistic computing approach is backed up by a practical experiment whose outcomes are presented in this article.
      Citation: Future Internet
      PubDate: 2019-02-01
      DOI: 10.3390/fi11020033
      Issue No: Vol. 11, No. 2 (2019)
  • Future Internet, Vol. 11, Pages 34: Fog vs. Cloud Computing: Should I Stay
           or Should I Go'

    • Authors: Flávia Pisani, Vanderson Martins do Rosario, Edson Borin
      First page: 34
      Abstract: In this article, we work toward the answer to the question “is it worth processing a data stream on the device that collected it or should we send it somewhere else'”. As it is often the case in computer science, the response is “it depends”. To find out the cases where it is more profitable to stay in the device (which is part of the fog) or to go to a different one (for example, a device in the cloud), we propose two models that intend to help the user evaluate the cost of performing a certain computation on the fog or sending all the data to be handled by the cloud. In our generic mathematical model, the user can define a cost type (e.g., number of instructions, execution time, energy consumption) and plug in values to analyze test cases. As filters have a very important role in the future of the Internet of Things and can be implemented as lightweight programs capable of running on resource-constrained devices, this kind of procedure is the main focus of our study. Furthermore, our visual model guides the user in their decision by aiding the visualization of the proposed linear equations and their slope, which allows them to find if either fog or cloud computing is more profitable for their specific scenario. We validated our models by analyzing four benchmark instances (two applications using two different sets of parameters each) being executed on five datasets. We use execution time and energy consumption as the cost types for this investigation.
      Citation: Future Internet
      PubDate: 2019-02-02
      DOI: 10.3390/fi11020034
      Issue No: Vol. 11, No. 2 (2019)
  • Future Internet, Vol. 11, Pages 35: Percolation and Internet Science

    • Authors: Franco Bagnoli, Emanuele Bellini, Emanuele Massaro, Raúl Rechtman
      First page: 35
      Abstract: Percolation, in its most general interpretation, refers to the “flow” of something (a physical agent, data or information) in a network, possibly accompanied by some nonlinear dynamical processes on the network nodes (sometimes denoted reaction–diffusion systems, voter or opinion formation models, etc.). Originated in the domain of theoretical and matter physics, it has many applications in epidemiology, sociology and, of course, computer and Internet sciences. In this review, we illustrate some aspects of percolation theory and its generalization, cellular automata and briefly discuss their relationship with equilibrium systems (Ising and Potts models). We present a model of opinion spreading, the role of the topology of the network to induce coherent oscillations and the influence (and advantages) of risk perception for stopping epidemics. The models and computational tools that are briefly presented here have an application to the filtering of tainted information in automatic trading. Finally, we introduce the open problem of controlling percolation and other processes on distributed systems.
      Citation: Future Internet
      PubDate: 2019-02-02
      DOI: 10.3390/fi11020035
      Issue No: Vol. 11, No. 2 (2019)
  • Future Internet, Vol. 11, Pages 36: Interoperability of the Time of
           Industry 4.0 and the Internet of Things

    • Authors: Francesco Lelli
      First page: 36
      Abstract: Industry 4.0 demands a dynamic optimization of production lines. They are formed by sets of heterogeneous devices that cooperate towards a shared goal. The Internet of Things can serve as a technology enabler for implementing such a vision. Nevertheless, the domain is struggling in finding a shared understanding of the concepts for describing a device. This aspect plays a fundamental role in enabling an “intelligent interoperability” among sensor and actuators that will constitute a dynamic Industry 4.0 production line. In this paper, we summarize the efforts of academics and practitioners toward describing devices in order to enable dynamic reconfiguration by machines or humans. We also propose a set of concepts for describing devices, and we analyze how present initiatives are covering these aspects.
      Citation: Future Internet
      PubDate: 2019-02-03
      DOI: 10.3390/fi11020036
      Issue No: Vol. 11, No. 2 (2019)
  • Future Internet, Vol. 11, Pages 37: Autonomic Network Management and
           Cross-Layer Optimization in Software Defined Radio Environments

    • Authors: Adamantia Stamou, Grigorios Kakkavas, Konstantinos Tsitseklis, Vasileios Karyotis, Symeon Papavassiliou
      First page: 37
      Abstract: The demand for Autonomic Network Management (ANM) and optimization is as intense as ever, even though significant research has been devoted towards this direction. This paper addresses such need in Software Defined (SDR) based Cognitive Radio Networks (CRNs). We propose a new framework for ANM and network reconfiguration combining Software Defined Networks (SDN) with SDR via Network Function Virtualization (NFV) enabled Virtual Utility Functions (VUFs). This is the first approach combining ANM with SDR and SDN via NFV, demonstrating how these state-of-the-art technologies can be effectively combined to achieve reconfiguration flexibility, improved performance and efficient use of available resources. In order to show the feasibility of the proposed framework, we implemented its main functionalities in a cross-layer resource allocation mechanism for CRNs over real SDR testbeds provided by the Orchestration and Reconfiguration Control Architecture (ORCA) EU project. We demonstrate the efficacy of our framework, and based on the obtained results, we identify aspects that can be further investigated for improving the applicability and increasing performance of our broader framework.
      Citation: Future Internet
      PubDate: 2019-02-03
      DOI: 10.3390/fi11020037
      Issue No: Vol. 11, No. 2 (2019)
  • Future Internet, Vol. 11, Pages 38: Research on a Support System for
           Automatic Ship Navigation in Fairway

    • Authors: Van Suong Nguyen
      First page: 38
      Abstract: In previous investigations, controllers for the track-keeping of ships were designed with the assumption of constant ship speed. However, when navigating in a fairway area, the ship’s speed is usually decreased to prepare for berthing. The existing track-keeping systems, which are applied when the ship navigates in the open sea with a constant ship speed, cannot be used to navigate the ship in the fairway. In this article, a support system is proposed for ship navigation in the fairway. This system performs three tasks. First, the ship is automatically controlled by regulating the rudder to follow planned tracks. Second, the ship’s speed is reduced step by step to approach the berth area at a low speed. Finally, at low speed, when the ship’s rudder is not effective enough to control the ship’s heading to a desired angle, the ship’s heading is adjusted appropriately by the bow thruster before changing the control mode into the automatic berthing system. By the proposed system, the automatic systems can be combined to obtain a fully automatic system for ship control. To validate the effectiveness of this proposed system for automatic ship navigation in the fairway, numerical simulations were conducted with a training ship model.
      Citation: Future Internet
      PubDate: 2019-02-03
      DOI: 10.3390/fi11020038
      Issue No: Vol. 11, No. 2 (2019)
  • Future Internet, Vol. 11, Pages 39: A Mathematical Model for Efficient and
           Fair Resource Assignment in Multipath Transport

    • Authors: Andreas Könsgen, Md. Shahabuddin, Amanpreet Singh, Anna Förster
      First page: 39
      Abstract: Multipath transport protocols are aimed at increasing the throughput of data flows as well as maintaining fairness between users, which are both crucial factors to maximize user satisfaction. In this paper, a mixed (non)linear programming (MINLP) solution is developed which provides an optimum solution to allocate link capacities in a network to a number of given traffic demands considering both the maximization of link utilization as well as fairness between transport layer data flows or subflows. The solutions of the MINLP formulation are evaluated w. r. t. their throughput and fairness using well-known metrics from the literature. It is shown that network flow fairness based capacity allocation achieves better fairness results than the bottleneck-based methods in most cases while yielding the same capacity allocation performance.
      Citation: Future Internet
      PubDate: 2019-02-10
      DOI: 10.3390/fi11020039
      Issue No: Vol. 11, No. 2 (2019)
  • Future Internet, Vol. 11, Pages 40: Audio-Visual Genres and Polymediation
           in Successful Spanish YouTubers

    • Authors: Torres Hortelano
      First page: 40
      Abstract: This paper is part of broader research entitled “Analysis of the YouTuber Phenomenon in Spain: An Exploration to Identify the Vectors of Change in the Audio-Visual Market”. My main objective was to determine the predominant audio-visual genres among the 10 most influential Spanish YouTubers in 2018. Using a quantitative extrapolation method, I extracted these data from SocialBlade, an independent website, whose main objective is to track YouTube statistics. Other secondary objectives in this research were to analyze: (1) Gender visualization, (2) the originality of these YouTube audio-visual genres with respect to others, and (3) to answer the question as to whether YouTube channels form a new audio-visual genre. I quantitatively analyzed these data to determine how these genres are influenced by the presence of polymediation as an integrated communicative environment working in relational terms with other media. My conclusion is that we can talk about a new audio-visual genre. When connected with polymediation, this may present an opportunity that has not yet been fully exploited by successful Spanish YouTubers.
      Citation: Future Internet
      PubDate: 2019-02-11
      DOI: 10.3390/fi11020040
      Issue No: Vol. 11, No. 2 (2019)
  • Future Internet, Vol. 11, Pages 41: A Scheme to Design Community Detection
           Algorithms in Various Networks

    • Authors: Haoye Lu, Amiya Nayak
      First page: 41
      Abstract: Network structures, consisting of nodes and edges, have applications in almost all subjects. A set of nodes is called a community if the nodes have strong interrelations. Industries (including cell phone carriers and online social media companies) need community structures to allocate network resources and provide proper and accurate services. However, most detection algorithms are derived independently, which is arduous and even unnecessary. Although recent research shows that a general detection method that serves all purposes does not exist, we believe that there is some general procedure of deriving detection algorithms. In this paper, we represent such a general scheme. We mainly focus on two types of networks: transmission networks and similarity networks. We reduce them to a unified graph model, based on which we propose a method to define and detect community structures. Finally, we also give a demonstration to show how our design scheme works.
      Citation: Future Internet
      PubDate: 2019-02-12
      DOI: 10.3390/fi11020041
      Issue No: Vol. 11, No. 2 (2019)
  • Future Internet, Vol. 11, Pages 42: 3D-CNN-Based Fused Feature Maps with
           LSTM Applied to Action Recognition

    • Authors: Sheeraz Arif, Jing Wang, Tehseen Ul Hassan, Zesong Fei
      First page: 42
      Abstract: Human activity recognition is an active field of research in computer vision with numerous applications. Recently, deep convolutional networks and recurrent neural networks (RNN) have received increasing attention in multimedia studies, and have yielded state-of-the-art results. In this research work, we propose a new framework which intelligently combines 3D-CNN and LSTM networks. First, we integrate discriminative information from a video into a map called a ‘motion map’ by using a deep 3-dimensional convolutional network (C3D). A motion map and the next video frame can be integrated into a new motion map, and this technique can be trained by increasing the training video length iteratively; then, the final acquired network can be used for generating the motion map of the whole video. Next, a linear weighted fusion scheme is used to fuse the network feature maps into spatio-temporal features. Finally, we use a Long-Short-Term-Memory (LSTM) encoder-decoder for final predictions. This method is simple to implement and retains discriminative and dynamic information. The improved results on benchmark public datasets prove the effectiveness and practicability of the proposed method.
      Citation: Future Internet
      PubDate: 2019-02-13
      DOI: 10.3390/fi11020042
      Issue No: Vol. 11, No. 2 (2019)
  • Future Internet, Vol. 11, Pages 43: Consistency Models of NoSQL Databases

    • Authors: Miguel Diogo, Bruno Cabral, Jorge Bernardino
      First page: 43
      Abstract: Internet has become so widespread that most popular websites are accessed by hundreds of millions of people on a daily basis. Monolithic architectures, which were frequently used in the past, were mostly composed of traditional relational database management systems, but quickly have become incapable of sustaining high data traffic very common these days. Meanwhile, NoSQL databases have emerged to provide some missing properties in relational databases like the schema-less design, horizontal scaling, and eventual consistency. This paper analyzes and compares the consistency model implementation on five popular NoSQL databases: Redis, Cassandra, MongoDB, Neo4j, and OrientDB. All of which offer at least eventual consistency, and some have the option of supporting strong consistency. However, imposing strong consistency will result in less availability when subject to network partition events.
      Citation: Future Internet
      PubDate: 2019-02-14
      DOI: 10.3390/fi11020043
      Issue No: Vol. 11, No. 2 (2019)
  • Future Internet, Vol. 11, Pages 44: BlackWatch: Increasing Attack
           Awareness within Web Applications

    • Authors: Calum C. Hall, Lynsay A. Shepherd, Natalie Coull
      First page: 44
      Abstract: Web applications are relied upon by many for the services they provide. It is essential that applications implement appropriate security measures to prevent security incidents. Currently, web applications focus resources towards the preventative side of security. While prevention is an essential part of the security process, developers must also implement a level of attack awareness into their web applications. Being able to detect when an attack is occurring provides applications with the ability to execute responses against malicious users in an attempt to slow down or deter their attacks. This research seeks to improve web application security by identifying malicious behavior from within the context of web applications using our tool BlackWatch. The tool is a Python-based application which analyzes suspicious events occurring within client web applications, with the objective of identifying malicious patterns of behavior. This approach avoids issues typically encountered with traditional web application firewalls. Based on the results from a preliminary study, BlackWatch was effective at detecting attacks from both authenticated and unauthenticated users. Furthermore, user tests with developers indicated BlackWatch was user-friendly, and was easy to integrate into existing applications. Future work seeks to develop the BlackWatch solution further for public release.
      Citation: Future Internet
      PubDate: 2019-02-15
      DOI: 10.3390/fi11020044
      Issue No: Vol. 11, No. 2 (2019)
  • Future Internet, Vol. 11, Pages 45: Tooth-Marked Tongue Recognition Using
           Gradient-Weighted Class Activation Maps

    • Authors: Yue Sun, Songmin Dai, Jide Li, Yin Zhang, Xiaoqiang Li
      First page: 45
      Abstract: The tooth-marked tongue is an important indicator in traditional Chinese medicinal diagnosis. However, the clinical competence of tongue diagnosis is determined by the experience and knowledge of the practitioners. Due to the characteristics of different tongues, having many variations such as different colors and shapes, tooth-marked tongue recognition is challenging. Most existing methods focus on partial concave features and use specific threshold values to classify the tooth-marked tongue. They lose the overall tongue information and lack the ability to be generalized and interpretable. In this paper, we try to solve these problems by proposing a visual explanation method which takes the entire tongue image as an input and uses a convolutional neural network to extract features (instead of setting a fixed threshold artificially) then classifies the tongue and produces a coarse localization map highlighting tooth-marked regions using Gradient-weighted Class Activation Mapping. Experimental results demonstrate the effectiveness of the proposed method.
      Citation: Future Internet
      PubDate: 2019-02-15
      DOI: 10.3390/fi11020045
      Issue No: Vol. 11, No. 2 (2019)
  • Future Internet, Vol. 11, Pages 46: Efficient Tensor Sensing for RF
           Tomographic Imaging on GPUs

    • Authors: Da Xu, Tao Zhang
      First page: 46
      Abstract: Radio-frequency (RF) tomographic imaging is a promising technique for inferring multi-dimensional physical space by processing RF signals traversed across a region of interest. Tensor-based approaches for tomographic imaging are superior at detecting the objects within higher dimensional spaces. The recently-proposed tensor sensing approach based on the transform tensor model achieves a lower error rate and faster speed than the previous tensor-based compress sensing approach. However, the running time of the tensor sensing approach increases exponentially with the dimension of tensors, thus not being very practical for big tensors. In this paper, we address this problem by exploiting massively-parallel GPUs. We design, implement, and optimize the tensor sensing approach on an NVIDIA Tesla GPU and evaluate the performance in terms of the running time and recovery error rate. Experimental results show that our GPU tensor sensing is as accurate as the CPU counterpart with an average of 44.79 × and up to 84.70 × speedups for varying-sized synthetic tensor data. For IKEA Model 3D model data of a smaller size, our GPU algorithm achieved 15.374× speedup over the CPU tensor sensing. We further encapsulate the GPU algorithm into an open-source library, called cuTensorSensing (CUDA Tensor Sensing), which can be used for efficient RF tomographic imaging.
      Citation: Future Internet
      PubDate: 2019-02-15
      DOI: 10.3390/fi11020046
      Issue No: Vol. 11, No. 2 (2019)
  • Future Internet, Vol. 11, Pages 47: Joint Optimal Power Allocation and
           Relay Selection Scheme in Energy Harvesting Two-Way Relaying Network

    • Authors: Song, Xu, Xie, Han
      First page: 47
      Abstract: In this paper, we propose a joint power allocation, time switching (TS) factor and relay selection scheme for an energy harvesting two-way relaying communication network (TWRN), where two transceivers exchange information with the help of a wireless-powered relay. By exploiting the TS architecture at the relay node, the relay node needs to use additional time slots for energy transmission, reducing the transmission rate. Thus, we propose a joint resource allocation algorithm to maximize the max-min bidirectional instantaneous information rate. To solve the original non-convex optimization problem, the objective function is decomposed into three sub-problems and solved sequentially. The closed-form solution of the transmit power of two sources and the optimal TS factor can be obtained by the information rate balancing technology and the proposed time allocation scheme, respectively. At last, the optimal relay node can be obtained. Simulation results show that the performance of the proposed algorithm is better than the traditional schemes and power-splitting (PS) scheme.
      Citation: Future Internet
      PubDate: 2019-02-15
      DOI: 10.3390/fi11020047
      Issue No: Vol. 11, No. 2 (2019)
  • Future Internet, Vol. 11, Pages 48: Vehicle Politeness in Driving

    • Authors: Jae-Gil Lee, Kwan Min Lee, Seoung-Ho Ryu
      First page: 48
      Abstract: Future vehicles are becoming more like driving partners instead of mere machines. With the application of advanced information and communication technologies (ICTs), vehicles perform driving tasks while drivers monitor the functioning states of vehicles. This change in interaction requires a deliberate consideration of how vehicles should present driving-related information. As a way of encouraging drivers to more readily accept instructions from vehicles, we suggest the use of social rules, such as politeness, in human-vehicle interaction. In a 2 × 2 between-subjects experiment, we test the effects of vehicle politeness (plain vs. polite) on drivers’ interaction experiences in two operation situations (normal vs. failure). The results indicate that vehicle politeness improves interaction experience in normal working situations but impedes the experience in failure situations. Specifically, in normal situations, vehicles with polite instructions are highly evaluated for social presence, politeness, satisfaction and intention to use. Theoretical and practical implications on politeness research and speech interaction design are discussed.
      Citation: Future Internet
      PubDate: 2019-02-16
      DOI: 10.3390/fi11020048
      Issue No: Vol. 11, No. 2 (2019)
  • Future Internet, Vol. 11, Pages 49: A Multi-Agent Architecture for Data

    • Authors: Gianfranco Lombardo, Paolo Fornacciari, Monica Mordonini, Michele Tomaiuolo, Agostino Poggi
      First page: 49
      Abstract: ActoDatA (Actor Data Analysis) is an actor-based software library for the development of distributed data mining applications. It provides a multi-agent architecture with a set of predefined and configurable agents performing the typical tasks of data mining applications. In particular, its architecture can manage different users’ applications; it maintains a high level of execution quality by distributing the agents of the applications on a dynamic set of computational nodes. Moreover, it provides reports about the analysis results and the collected data, which can be accessed through either a web browser or a dedicated mobile APP. After an introduction about the actor model and the software framework used for implementing the software library, this article underlines the main features of ActoDatA and presents its experimentation in some well-known data analysis domains.
      Citation: Future Internet
      PubDate: 2019-02-18
      DOI: 10.3390/fi11020049
      Issue No: Vol. 11, No. 2 (2019)
  • Future Internet, Vol. 11, Pages 50: Minimum Viable Products for Internet
           of Things Applications: Common Pitfalls and Practices

    • Authors: Anh Nguyen-Duc, Khan Khalid, Sohaib Shahid Bajwa, Tor Lønnestad
      First page: 50
      Abstract: Internet of Things applications are not only the new opportunity for digital businesses but also a major driving force for the modification and creation of software systems in all industries and businesses. Compared to other types of software-intensive products, the development of Internet of Things applications lacks a systematic approach and guidelines. This paper aims at understanding the common practices and challenges among start-up companies who are developing Internet of Things products. A qualitative research is conducted with data from twelve semi-structured interviews. A thematic analysis reveals common types of Minimum Viable Products, prototyping techniques and production concerns among early stage hardware start-ups. We found that hardware start-ups go through an incremental prototyping process toward production. The progress associates with the transition from speed-focus to quality-focus. Hardware start-ups heavily rely on third-party vendors in term of development speed and final product quality. We identified 24 challenges related to management, requirement, design, implementation and testing. Internet of Things entrepreneurs should be aware of relevant pitfalls and managing both internal and external risks.
      Citation: Future Internet
      PubDate: 2019-02-18
      DOI: 10.3390/fi11020050
      Issue No: Vol. 11, No. 2 (2019)
  • Future Internet, Vol. 11, Pages 51: A Fusion Load Disaggregation Method
           Based on Clustering Algorithm and Support Vector Regression Optimization
           for Low Sampling Data

    • Authors: Quanbo Yuan, Huijuan Wang, Botao Wu, Yaodong Song, Hejia Wang
      First page: 51
      Abstract: In order to achieve more efficient energy consumption, it is crucial that accurate detailed information is given on how power is consumed. Electricity details benefit both market utilities and also power consumers. Non-intrusive load monitoring (NILM), a novel and economic technology, obtains single-appliance power consumption through a single total power meter. This paper, focusing on load disaggregation with low hardware costs, proposed a load disaggregation method for low sampling data from smart meters based on a clustering algorithm and support vector regression optimization. This approach combines the k-median algorithm and dynamic time warping to identify the operating appliance and retrieves single energy consumption from an aggregate smart meter signal via optimized support vector regression (OSVR). Experiments showed that the technique can recognize multiple devices switching on at the same time using low-frequency data and achieve a high load disaggregation performance. The proposed method employs low sampling data acquired by smart meters without installing extra measurement equipment, which lowers hardware cost and is suitable for applications in smart grid environments.
      Citation: Future Internet
      PubDate: 2019-02-19
      DOI: 10.3390/fi11020051
      Issue No: Vol. 11, No. 2 (2019)
  • Future Internet, Vol. 11, Pages 52: Sentiment Analysis Based Requirement
           Evolution Prediction

    • Authors: Lingling Zhao, Anping Zhao
      First page: 52
      Abstract: To facilitate product developers capturing the varying requirements from users to support their feature evolution process, requirements evolution prediction from massive review texts is in fact of great importance. The proposed framework combines a supervised deep learning neural network with an unsupervised hierarchical topic model to analyze user reviews automatically for product feature requirements evolution prediction. The approach is to discover hierarchical product feature requirements from the hierarchical topic model and to identify their sentiment by the Long Short-term Memory (LSTM) with word embedding, which not only models hierarchical product requirement features from general to specific, but also identifies sentiment orientation to better correspond to the different hierarchies of product features. The evaluation and experimental results show that the proposed approach is effective and feasible.
      Citation: Future Internet
      PubDate: 2019-02-21
      DOI: 10.3390/fi11020052
      Issue No: Vol. 11, No. 2 (2019)
  • Future Internet, Vol. 11, Pages 53: Embedded Deep Learning for Ship
           Detection and Recognition

    • Authors: Hongwei Zhao, Weishan Zhang, Haoyun Sun, Bing Xue
      First page: 53
      Abstract: Ship detection and recognition are important for smart monitoring of ships in order to manage port resources effectively. However, this is challenging due to complex ship profiles, ship background, object occlusion, variations of weather and light conditions, and other issues. It is also expensive to transmit monitoring video in a whole, especially if the port is not in a rural area. In this paper, we propose an on-site processing approach, which is called Embedded Ship Detection and Recognition using Deep Learning (ESDR-DL). In ESDR-DL, the video stream is processed using embedded devices, and we design a two-stage neural network named DCNet, which is composed of a DNet for ship detection and a CNet for ship recognition, running on embedded devices. We have extensively evaluated ESDR-DL, including performance of accuracy and efficiency. The ESDR-DL is deployed at the Dongying port of China, which has been running for over a year and demonstrates that it can work reliably for practical usage.
      Citation: Future Internet
      PubDate: 2019-02-21
      DOI: 10.3390/fi11020053
      Issue No: Vol. 11, No. 2 (2019)
  • 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 21: An Explorative Model to Assess
           Individuals’ Phubbing Risk

    • Authors: Andrea Guazzini, Mirko Duradoni, Ambra Capelli, Patrizia Meringolo
      First page: 21
      Abstract: Phubbing could be defined as a new form of addiction; however, checking the phone and ignoring the speaker could also be linked to the increased availability of virtual social environments. We developed a multidimensional model for phubbing considering psychological dimensions and information and communication technology related habits. We collected data through online questionnaires and surveys. The best model obtained from our data was constituted by Information and Communication Technologies’ (ICTs) usage behaviours, Trait Anxiety, Virtual Sense of Community and Neuroticism. Finally, our study confirmed a strong connection between phubbing and online addiction behaviours.
      Citation: Future Internet
      PubDate: 2019-01-18
      DOI: 10.3390/fi11010021
      Issue No: Vol. 11, No. 1 (2019)
  • Future Internet, Vol. 11, Pages 22: Improved Arabic–Chinese Machine
           Translation with Linguistic Input Features

    • Authors: Fares Aqlan, Xiaoping Fan, Abdullah Alqwbani, Akram Al-Mansoub
      First page: 22
      Abstract: This study presents linguistically augmented models of phrase-based statistical machine translation (PBSMT) using different linguistic features (factors) on the top of the source surface form. The architecture addresses two major problems occurring in machine translation, namely the poor performance of direct translation from a highly-inflected and morphologically complex language into morphologically poor languages, and the data sparseness issue, which becomes a significant challenge under low-resource conditions. We use three factors (lemma, part-of-speech tags, and morphological features) to enrich the input side with additional information to improve the quality of direct translation from Arabic to Chinese, considering the importance and global presence of this language pair as well as the limitation of work on machine translation between these two languages. In an effort to deal with the issue of the out of vocabulary (OOV) words and missing words, we propose the best combination of factors and models based on alternative paths. The proposed models were compared with the standard PBSMT model which represents the baseline of this work, and two enhanced approaches tokenized by a state-of-the-art external tool that has been proven to be useful for Arabic as a morphologically rich and complex language. The experiment was performed with a Moses decoder on freely available data extracted from a multilingual corpus from United Nation documents (MultiUN). Results of a preliminary evaluation in terms of BLEU scores show that the use of linguistic features on the Arabic side considerably outperforms baseline and tokenized approaches, the system can consistently reduce the OOV rate as well.
      Citation: Future Internet
      PubDate: 2019-01-19
      DOI: 10.3390/fi11010022
      Issue No: Vol. 11, No. 1 (2019)
  • Future Internet, Vol. 11, Pages 23: Surveying Human Habit Modeling and
           Mining Techniques in Smart Spaces

    • Authors: Francesco Leotta, Massimo Mecella, Daniele Sora, Tiziana Catarci
      First page: 23
      Abstract: A smart space is an environment, mainly equipped with Internet-of-Things (IoT) technologies, able to provide services to humans, helping them to perform daily tasks by monitoring the space and autonomously executing actions, giving suggestions and sending alarms. Approaches suggested in the literature may differ in terms of required facilities, possible applications, amount of human intervention required, ability to support multiple users at the same time adapting to changing needs. In this paper, we propose a Systematic Literature Review (SLR) that classifies most influential approaches in the area of smart spaces according to a set of dimensions identified by answering a set of research questions. These dimensions allow to choose a specific method or approach according to available sensors, amount of labeled data, need for visual analysis, requirements in terms of enactment and decision-making on the environment. Additionally, the paper identifies a set of challenges to be addressed by future research in the field.
      Citation: Future Internet
      PubDate: 2019-01-19
      DOI: 10.3390/fi11010023
      Issue No: Vol. 11, No. 1 (2019)
  • Future Internet, Vol. 11, Pages 24: Simple and Efficient Computational
           Intelligence Strategies for Effective Collaborative Decisions

    • Authors: Emelia Opoku Aboagye, Rajesh Kumar
      First page: 24
      Abstract: We approach scalability and cold start problems of collaborative recommendation in this paper. An intelligent hybrid filtering framework that maximizes feature engineering and solves cold start problem for personalized recommendation based on deep learning is proposed in this paper. Present e-commerce sites mainly recommend pertinent items or products to a lot of users through personalized recommendation. Such personalization depends on large extent on scalable systems which strategically responds promptly to the request of the numerous users accessing the site (new users). Tensor Factorization (TF) provides scalable and accurate approach for collaborative filtering in such environments. In this paper, we propose a hybrid-based system to address scalability problems in such environments. We propose to use a multi-task approach which represent multiview data from users, according to their purchasing and rating history. We use a Deep Learning approach to map item and user inter-relationship to a low dimensional feature space where item-user resemblance and their preferred items is maximized. The evaluation results from real world datasets show that, our novel deep learning multitask tensor factorization (NeuralFil) analysis is computationally less expensive, scalable and addresses the cold-start problem through explicit multi-task approach for optimal recommendation decision making.
      Citation: Future Internet
      PubDate: 2019-01-21
      DOI: 10.3390/fi11010024
      Issue No: Vol. 11, No. 1 (2019)
  • Future Internet, Vol. 11, Pages 25: Smart System for Prediction of
           Accurate Surface Electromyography Signals Using an Artificial Neural

    • Authors: Osama Dorgham, Ibrahim Al-Mherat, Jawdat Al-Shaer, Sulieman Bani-Ahmad, Stephen Laycock
      First page: 25
      Abstract: Bioelectric signals are used to measure electrical potential, but there are different types of signals. The electromyography (EMG) is a type of bioelectric signal used to monitor and recode the electrical activity of the muscles. The current work aims to model and reproduce surface EMG (SEMG) signals using an artificial neural network. Such research can aid studies into life enhancement for those suffering from damage or disease affecting their nervous system. The SEMG signal is collected from the surface above the bicep muscle through dynamic (concentric and eccentric) contraction with various loads. In this paper, we use time domain features to analyze the relationship between the amplitude of SEMG signals and the load. We extract some features (e.g., mean absolute value, root mean square, variance and standard deviation) from the collected SEMG signals to estimate the bicep’ muscle force for the various loads. Further, we use the R-squared value to depict the correlation between the SEMG amplitude and the muscle loads by linear fitting. The best performance the ANN model with 60 hidden neurons for three loads used (3 kg, 5 kg and 7 kg) has given a mean square error of 1.145, 1.3659 and 1.4238, respectively. The R-squared observed are 0.9993, 0.99999 and 0.99999 for predicting (reproduction step) of smooth SEMG signals.
      Citation: Future Internet
      PubDate: 2019-01-21
      DOI: 10.3390/fi11010025
      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)
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