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<html><head><title>EAI Endorsed Transactions on Industrial Networks and Intelligent Systems - EUDL</title><link rel="icon" href="/images/favicon.ico"><link rel="stylesheet" type="text/css" href="/css/screen.css"><link rel="stylesheet" href="/css/zenburn.css"><meta http-equiv="Content-Type" content="charset=utf-8"><meta name="viewport" content="width=device-width, initial-scale=1.0"><meta name="Description" content="Visit the new journal website to submit and consult our contents: https://publications.eai.eu/index.php/inis/index"><script type="text/javascript" src="https://services.eai.eu//load-signup-form/EAI"></script><script type="text/javascript" src="https://services.eai.eu//ujs/forms/signup/sso-client.js"></script><script type="text/javascript">if (!window.EUDL){ window.EUDL={} };EUDL.cas_url="https://account.eai.eu/cas";EUDL.profile_url="https://account.eai.eu";if(window.SSO){SSO.set_mode('eai')};</script><script type="text/javascript" src="/js/jquery.js"></script><script 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1</a></div></div></section></section><section class="info-and-search"><div class="manage-menu"></div><a href="/journal/inis"><h1>EAI Endorsed Transactions on Industrial Networks and Intelligent Systems</h1></a><section class="issue-number">Issue 21, 2019</section><section class="editors"><strong>Editor(s)-in-Chief: </strong><span class="editor">Trung Q. Duong</span> and <span class="editor">Le Nguyen Bao</span></section><section class="issue-tabs"><div class="tabs"><ul><li><a name="articles">Articles</a></li><li><a name="meta">Information</a></li></ul></div><div class="content"><div name="articles"><section id="publications-results" class="search-results"><ul class="results-list"><li class="result-item article-light first"><h3><a href="/doi/10.4108/eai.13-7-2018.160389">A Secure Authentication Scheme based on Brownian Motion in hierarchy Wireless Sensor Networks</a></h3><dl class="metadata"><dt class="title">Appears in: </dt><dd class="value">inis<span class="info-separator"> </span><strong>19</strong><span class="info-separator">(</span>21<span class="info-separator">)</span><span class="info-separator">: </span>e1</dd><br><dt class="title">Authors: </dt><dd class="value">Minh Hoang Trong, Ngoc Le Van, Nguyen Lang Tuan, Hai Hoang Dang</dd><br><dt class="title">Abstract: </dt><dd class="value abstract"><span class="shortened">In the last few years, the Internet of Things (IoT) has experienced exponential advancements. In IoT infrastructures, Wireless Sensor Network (WSN) has been considered as one of the crucial technologies to support a lot of amazing services. To fulfill new requirements of deployed network environm…</span><span class="full">In the last few years, the Internet of Things (IoT) has experienced exponential advancements. In IoT <br>infrastructures, Wireless Sensor Network (WSN) has been considered as one of the crucial technologies to <br>support a lot of amazing services. To fulfill new requirements of deployed network environments, the security issue in wireless sensor networks has to be met new challenges such as secured and lightweight requirements simultaneously. Hence, in this paper, an authentication scheme based on the watermarking technique is proposed to secure the sensory data in hierarchy wireless sensor networks. Especially, natural movement characteristics of a sensor node are exploited to provide a conveniently watermarked data, that can be used to validate and detect data integrity attacks in familiar methods. The proposed authentication scheme is evaluated by numerical results and theoretically analyzed to prove a proposal efficiency.<br></span> <span class="expander more"><a class="trigger">more »</a></span></dd></dl></li><li class="result-item article-light"><h3><a href="/doi/10.4108/eai.24-10-2019.160982">Transmit Antenna Selection Aided Linear Group Precoding for Massive MIMO Systems</a></h3><dl class="metadata"><dt class="title">Appears in: </dt><dd class="value">inis<span class="info-separator"> </span><strong>19</strong><span class="info-separator">(</span>21<span class="info-separator">)</span><span class="info-separator">: </span>e2</dd><br><dt class="title">Authors: </dt><dd class="value">Van Khoi Dinh, Minh Tuan Le, Vu Duc Ngo, Xuan Nam Tran, Chi Hieu Ta</dd><br><dt class="title">Abstract: </dt><dd class="value abstract"><span class="shortened">In this paper, we investigate the combination of linear group precoding with a transmit antenna group selection (TA-GS) algorithm based on the channel capacity analysis for Massive MIMO systems. Simultaneously, we propose a low complexity linear precoding algorithm that works on the selected antenn…</span><span class="full">In this paper, we investigate the combination of linear group precoding with a transmit antenna group selection (TA-GS) algorithm based on the channel capacity analysis for Massive MIMO systems. Simultaneously, we propose a low complexity linear precoding algorithm that works on the selected antennas. The proposed precoder is developed based on the conventional linear precoders in combination with the element-base lattice reduction shortest longest vector technique having low complexity. Numerical and simulation results show that the system performance significantly improves when the transmit selection technique is applied. Besides, the proposed precoder has remarkably lower computational complexity than its LC-RBD-LR-ZF counterpart. The bit error rate (BER) performance of the proposed precoder can approach that of the LC-RBD-LR-ZF precoder as the number of groups increases, yet at the cost of higher detection <br>complexity.<br></span> <span class="expander more"><a class="trigger">more »</a></span></dd></dl></li><li class="result-item article-light"><h3><a href="/doi/10.4108/eai.24-10-2019.160983">All-Digital Background Calibration Technique for Offset, Gain and Timing Mismatches in Time-Interleaved ADCs</a></h3><dl class="metadata"><dt class="title">Appears in: </dt><dd class="value">inis<span class="info-separator"> </span><strong>19</strong><span class="info-separator">(</span>21<span class="info-separator">)</span><span class="info-separator">: </span>e3</dd><br><dt class="title">Authors: </dt><dd class="value">Van-Thanh Ta, Van-Phuc Hoang, Xuan Nam Tran</dd><br><dt class="title">Abstract: </dt><dd class="value abstract"><span class="shortened">This paper presents a method for all-digital background calibration of multiple channel mismatches including offset, gain and timing mismatches in time-interleaved analog to digital converters (TIADCs). The averaging technique is used to remove the offset mismatch at each channel. The gain mismatch…</span><span class="full">This paper presents a method for all-digital background calibration of multiple channel mismatches including offset, gain and timing mismatches in time-interleaved analog to digital converters (TIADCs). The averaging technique is used to remove the offset mismatch at each channel. The gain mismatch is calibrated by calculating the power ratio of the subADC over the reference ADC. Timing skew is compensated by using Hadamard transform for error correction and least <br>mean squares (LMS) algorithm for estimation of the clock skew. The performance improvement of TIADCs employing these techniques is demonstrated through numerical simulations.<br></span> <span class="expander more"><a class="trigger">more »</a></span></dd></dl></li><li class="result-item article-light"><h3><a href="/doi/10.4108/eai.24-10-2019.160984">A Simulation Analysis of the Connectivity of Multi-hop Path between Two Arbitrary Nodes in Cognitive Radio Ad Hoc Networks</a></h3><dl class="metadata"><dt class="title">Appears in: </dt><dd class="value">inis<span class="info-separator"> </span><strong>19</strong><span class="info-separator">(</span>21<span class="info-separator">)</span><span class="info-separator">: </span>e4</dd><br><dt class="title">Authors: </dt><dd class="value">Le The Dung, Ba Cao Nguyen, Tran Manh Hoang</dd><br><dt class="title">Abstract: </dt><dd class="value abstract"><span class="shortened">The connectivity of multi-hop path is one of the key factors that influence the performance of multi-hop wireless networks. In this paper, assuming that secondary users (SUs) and primary users (PUs), using same licensed frequency bands, are uniformly distributed in square network area, we investiga…</span><span class="full">The connectivity of multi-hop path is one of the key factors that influence the performance of multi-hop wireless networks. In this paper, assuming that secondary users (SUs) and primary users (PUs), using same licensed frequency bands, are uniformly distributed in square network area, we investigate the connectivity of multi-hop path in cognitive radio ad-hoc <br>networks (CRAHNs). Specifically, we propose an algorithm to find all available multi-hop paths between arbitrary source node and destination node in CRAHNs with random node distribution and PU activity. Then, we use statistical simulation method to intensively evaluate the connectivity of multi-hop path compared with that in conventional ad-hoc networks (AHNs) by using huge number of random network topologies with different network parameters such as the number of SUs and PUs, network size, network operating frequency, and the average active rates of PU. The simulation results reveal many interesting and distinguishing features of the connectivity of multi-hop path in CRAHNs. Moreover, from the simulation graphs in this paper, network designers can select optimal network parameters so that the reliability of network <br>topology is high while saving network resources. Finally, the simulation results can be used to verify mathematical models of the connectivity of multi-hop path in CRAHNs in future research.<br></span> <span class="expander more"><a class="trigger">more »</a></span></dd></dl></li><li class="result-item article-light"><h3><a href="/doi/10.4108/eai.24-10-2019.160985">Quality of Service Provisioning for D2D Users in Heterogeneous Networks</a></h3><dl class="metadata"><dt class="title">Appears in: </dt><dd class="value">inis<span class="info-separator"> </span><strong>19</strong><span class="info-separator">(</span>21<span class="info-separator">)</span><span class="info-separator">: </span>e5</dd><br><dt class="title">Authors: </dt><dd class="value">Tien Hoa Nguyen, Dang Qua Nguyen, Viet Dung Nguyen</dd><br><dt class="title">Abstract: </dt><dd class="value abstract"><span class="shortened">This paper investigates power allocation for D2D communications in a Heterogeneous Network (HetNet) which includes a macro cell and pico cells, whereas femto cells are distributed inside. The objective is to minimize the total power consumption of D2D transmitter while satisfying a set of Quality…</span><span class="full">This paper investigates power allocation for D2D communications in a Heterogeneous Network (HetNet) <br>which includes a macro cell and pico cells, whereas femto cells are distributed inside. The objective is to <br>minimize the total power consumption of D2D transmitter while satisfying a set of Quality of Service in <br>D2D receivers and cellular users communication interference. To this end, we first obtain expression for the <br>formula of signal to interference plus noise ratio (SINR) and spectral efficiency of each D2D receiver. Then, <br>an optimization problem is formulated to minimize the total transmit power of D2D transmitters subject to <br>QoS constraints. It is shown that this optimization problem is linear programming and it can be solved in <br>polynomial time with standard tools. In addition, the maximization value of D2D pair transmission rates are <br>determined with fixed cellular users parameters.<br></span> <span class="expander more"><a class="trigger">more »</a></span></dd></dl></li></ul></section></div><div name="meta"><h2>Scope</h2><div class="abstract"><div class="shortened"><p>Along with the fast development of computer technologies, e.g., ubiquitous computing, cloud computing and cyber-physical system, all kinds of networks (e.g., control network, communication network, sensor network, body area network, social network, opportunistic network, cloud-based network, etc.) …</p></div><div class="full"><p>Along with the fast development of computer technologies, e.g., ubiquitous computing, cloud computing and cyber-physical system, all kinds of networks (e.g., control network, communication network, sensor network, body area network, social network, opportunistic network, cloud-based network, etc.) appeared and were applied in large-scale factories, including a lot of traditional and new industries, e.g., textile industry, coal industry, mining industry, steel industry, machinery industry, petrochemical industry, and biomedical industry, etc. Assisted by various industrial networks, automation in industry can reduce cost greatly because it takes advantage of control systems and information technologies to optimize productivity in the production of goods and delivery of services. However, the industrial environment is dynamic and harsh usually, including extreme temperature, humidity, electromagnetic interference and vibration, which proposed specific requirements to intelligent industrial systems under certain circumstances. All these highlight the criticality of the design, analysis and implementation of intelligent industrial systems.</p></div> <span class="expander more"><a class="trigger">more »</a></span></div><h2>Topics</h2><div class="abstract"><div class="shortened"><ul> <li>Applications of wireless sensor networks, body area networks in large-scale industrial applications, such as fault theories of wireless networks, including routing, network control and management, reliable transmission and architectures, etc.</li> <li>Applications of social networking, big data, ubiqui…</li> </ul></div><div class="full"><ul> <li>Applications of wireless sensor networks, body area networks in large-scale industrial applications, such as fault theories of wireless networks, including routing, network control and management, reliable transmission and architectures, etc.</li> <li>Applications of social networking, big data, ubiquitous computing, mobile computing, and cloud computing in various industries and services (e.g., intelligent systems enhanced by social networking, cloud-based industrial networks, cloud-assisted intelligent systems, etc.)</li> <li>Analysis of industrial control and communication networks, including network lifetime, security, network scalability, reliability, stability, etc.</li> <li>Design and choice of industrial, intelligent, application-specific network protocols and algorithms (e.g., EtherNet/IP, Ethernet Powerlink, EtherCAT, Modbus-TCP, Profinet, SERCOS III, etc.) at any communication layer</li> <li>Opportunistic networks in the industry, such as underwater sensor networks in sewage treatment systems, including establishing a temporary data transmission structure using available devices (e.g., underwater robot, surface data station, surface sink and under water sink), optimizing horizontal multi-hop data links (e.g., 3D data transmission), etc.</li> <li>Applications of intelligent systems in various industries, including collaborative systems, quality control, optimization, decision support, planning, high-level control concepts (e.g., multi-agent and holonic systems, service-oriented architectures), low-level control concepts (e.g., IEC 61131-3 and IEC 61499-based control), advanced system engineering concepts (e.g., model-driven development, component-based design), supply chains, value chains, virtual organizations, and virtual societies, emergency preparedness, crisis management, business channels, electronic marketplaces, enterprise resources planning, etc.</li> <li>Design and analysis of real-time embedded industrial systems, including real-time computing, real-time operating systems, real-time communications, networked embedded systems technology, etc.</li> <li>Novel control techniques, with respect to process control, equipment control, supervisory control, adaptive control, motion control, etc.</li> <li>Automated manufacturing systems, regarding formal modeling and analysis of manufacturing systems, scheduling of manufacturing systems, queuing systems and petri nets in manufacturing systems, etc.</li> <li>Computational intelligence in automation, including neural, fuzzy, evolutionary approaches in automation, ant colonies optimization and swarm intelligence in automation, machine learning, expert systems, etc.</li> <li>Hardware and software design and development for intelligent systems, such as intelligent and humanized production monitoring and control, etc.</li> <li>Big data analysis and processing in various industries and services, including constructing data analysis models, providing data analysis and processing tools and designing various optimization algorithms based on data analysis.</li> <li>Crowd-sourced behavior analysis in various industry and services, such as measuring and calculating the diffusion direction and speed of gas in the petrochemical industry based on crowd-sourced data from a large number of and various types of sensors, as well as product and service evaluation.</li> <li>Simulation and testbed of current industrial networks and intelligent systems, including network performance analysis, automated manufacturing, intelligent monitoring, disaster prevention, etc.</li> <li>Vision of future smart factories, service, marketing, and their integration, incorporating current existing technologies.</li> <li>Multimedia applications, content management, process management and knowledge management for various industries, services, and engineering education: including multimedia processing, multimedia retrieval, multimedia indexing, image sensing, image processing, image coding, image recognition, etc.</li> <li>Pattern recognition methods for various industries and services: including statistical theory, clustering, similarity measures, unsupervised learning, supervised learning, etc.</li> <li>Survey, review and essay of current industrial networks researches and intelligent systems development.</li> </ul></div> <span class="expander more"><a class="trigger">more »</a></span></div><h2>Indexing</h2><div class="abstract"><div class="shortened"><ul> <li><a href="https://www.scopus.com/sourceid/21101049547">Scopus</a></li> <li><a href="https://doaj.org/toc/2410-0218">DOAJ</a></li> <li><a href="https://dblp.uni-trier.de/db/journals/inis/">DBLP</a></li> <li><a href="https://search.crossref.org/?q=2410-0218">CrossRef</a></li> <li>[OCLC Discovery Services](https://www.worldcat.org/search?q=eai+endorsed+tran…</li> </ul></div><div class="full"><ul> <li><a href="https://www.scopus.com/sourceid/21101049547">Scopus</a></li> <li><a href="https://doaj.org/toc/2410-0218">DOAJ</a></li> <li><a href="https://dblp.uni-trier.de/db/journals/inis/">DBLP</a></li> <li><a href="https://search.crossref.org/?q=2410-0218">CrossRef</a></li> <li><a href="https://www.worldcat.org/search?q=eai+endorsed+transactions+on+industrial+networks&qt=owc_search">OCLC Discovery Services</a></li> <li><a href="https://europub.co.uk/journals/8120">EuroPub</a></li> <li><a href="https://publons.com/journal/29023/eai-endorsed-transactions-on-industrial-networks-a">Publons</a></li> <li><a href="https://app.dimensions.ai/discover/publication?or_facet_source_title=jour.1152852">Dimensions</a></li> <li><a href="https://www.proquest.com/products-services/Publicly-Available-Content-Database.html#overviewlinkSection">Publicly Available Content Database (ProQuest)</a></li> <li><a href="https://www.proquest.com/products-services/adv_tech_aero.html">Advanced Technologies & Aerospace Database (ProQuest)</a></li> <li><a href="https://www.proquest.com/products-services/adv_tech_aero.html">SciTech Premium Collection (ProQuest)</a></li> <li><a href="https://scholar.google.sk/scholar?as_ylo=2018&q=source:EAI+source:Endorsed+source:Transactions+source:on+source:Industrial+source:Networks+source:and+source:Intelligent+source:Systems&hl=es&as_sdt=0,5">Google Scholar</a></li> </ul></div> <span class="expander more"><a class="trigger">more »</a></span></div><h2>Editorial Board</h2><div class="abstract"><div class="shortened"><ul> <li>Ala Al-Fuqaha (Western Michigan University, USA)</li> <li>Al-Sakib Khan Pathan (Southeast University, Bangladesh)</li> <li>Ammar Rayes (Cisco Systems, USA)</li> <li>Antonino Masaracchia (IIT-CNR, Italy)</li> <li>Athanasios Maglaras (Dr, Prof . ofT.E.I. of Larissa)</li> <li>Berk Canberk (Northeastern University, USA)</li> <li>Ca V. Phan (…</li> </ul></div><div class="full"><ul> <li>Ala Al-Fuqaha (Western Michigan University, USA)</li> <li>Al-Sakib Khan Pathan (Southeast University, Bangladesh)</li> <li>Ammar Rayes (Cisco Systems, USA)</li> <li>Antonino Masaracchia (IIT-CNR, Italy)</li> <li>Athanasios Maglaras (Dr, Prof . ofT.E.I. of Larissa)</li> <li>Berk Canberk (Northeastern University, USA)</li> <li>Ca V. Phan (Ho Chi Minh City University of Technology and Education, Vietnam)</li> <li>Chau Yuen (Singapore University of Technology and Design, Singapore)</li> <li>Chengfei Liu (Swinburne University of Technology, Australia)</li> <li>Chinmoy Kundu (University of Texas at Dallas, USA)</li> <li>Christer Carlsson (Åbo Akademi University, Finland)</li> <li>Chunsheng Zhu (University of British Columbia)</li> <li>Constandinos Mavromoustakis (University of Nicosia, Cyprus)</li> <li>Der-Jiunn Deng (National Changhua University of Education, Taiwan)</li> <li>Dickson Chiu (The University of Hong Kong)</li> <li>Eleanna Kafeza (Athens University of Economics and Business, Greece)</li> <li>Fu-ren Lin (National Tsing Hua University, Taiwan)</li> <li>Gerhard Hancke (University of London, UK)</li> <li>Guangjie Han (Hohai University, China)</li> <li>Guojun Wang (Central South University, China)</li> <li>Hacene Fouchal (University of Reims Champagne-Ardenne, France)</li> <li>Haklae Kim (Chung-Ang University, South Korea)</li> <li>Halil Yetgin (Bitlis Eren University, Turkey)</li> <li>Hideyasu Sasaki (Ritsumeikan University, Kyoto, Japan)</li> <li>Ho-fung Leung (Chinese University of Hong Kong, Hong Kong)</li> <li>Honggang Wang (University of Massachusetts Dartmouth, USA)</li> <li>Hua Hu (Hangzhou Dianzi University, China)</li> <li>Ibrahim Kushchu (Mobile Government Consortium International, UK)</li> <li>Irene Kafeza (Irene Law Office, Greece)</li> <li>Isabelle Comyn-Wattiau (ESSEC Business School Paris, France)</li> <li>Jaime Lloret- Mauri (Universitat Politècnica de València, Spain)</li> <li>Javier M. Aguiar (Universidad de Valladolid, Valladolid, Spain)</li> <li>Jesus Alonso-Zarate (Telecommunications Technology Center of Catalonia, Spain)</li> <li>Jian Yang (Macquarie University, Australia)</li> <li>Jiankun Hu (University of New South Wales, Australia)</li> <li>Jianmin Jiang (Shenzhen University)</li> <li>Jianwei Niu (Beihang University, China)</li> <li>Jinlei Jiang (Tsinghua University, China)</li> <li>Jinsong Wu (Bell Laboratory, China)</li> <li>Joel Rodrigues (Inst. Telecomunicações, Univ. of Beira Interior, Portugal)</li> <li>Juan Trujillo (University of Alicante, Spain)</li> <li>Jucheng Yang (Tianjing University of Technology, China)</li> <li>Junqing Zhang (Queen's University Belfast)</li> <li>KUN WANG (Nanjing University of Posts and Telecommunications)</li> <li>Kuo-Ming Chao (Leader – Distributed Systems and Modelling Research Group, UK)</li> <li>Leandros A. Maglaras (De Montfort University, UK)</li> <li>Lei Wang (Dalian University of Technology, China)</li> <li>Liang Zhou (Nanjing University of Posts and Telecommunications, China)</li> <li>Long D. Nguyen (Dong Nai University, Vietnam)</li> <li>Maggie M. Wang (The University of Hong Kong, Hong Kong)</li> <li>Nghia Duong-Trung (German Research Center for Artificial Intelligence, Germany)</li> <li>Ngo Hoang Tu (Seoul National University of Science and Technology, South Korea)</li> <li>Nguyen Van Nam (Viettel, Vietnam)</li> <li>Nicholas C Romano (Oklahoma State University, USA)</li> <li>Noel Crespi (Institut Mines-Telecom, Telecom SudParis, France)</li> <li>Panlong Yang (PLA University of Science and Technology, China)</li> <li>Pasi Tyrväinen (University of Jyväskylä, Finland)</li> <li>Patrick C.K. Hung (University of Ontario Institute of Technology, Canada)</li> <li>Periklis Chatzimisios (Alexander TEI of Thessaloniki, Greece)</li> <li>Pierluigi Siano (Università degli Studi di Salerno, Italy)</li> <li>Pirkko Walden (Abo Akademi University, Finland)</li> <li>Phuong Bui (Duy Tan University, Vietnam)</li> <li>Raymond Y.K Lau (City University of Hong Kong, Hong Kong)</li> <li>Richard Yu (Carleton University, Canada)</li> <li>Rong Yu (Guangdong University of Technology, China)</li> <li>Rose Hu (Utah State University, USA)</li> <li>Sammy Chan (City University of HongKong, HK)</li> <li>Shing-Chi Cheung (Hong Kong University of Science and Technology, Hong Kong)</li> <li>Stephen J. H. Yang (National Central University, Taiwan)</li> <li>Syed Hassan Ahmed (University of Central Florida, USA)</li> <li>Thanh-Phuong Nguyen (University of Toulon, France)</li> <li>Tran Trung Duy (PTIT, VietNam)</li> <li>Trang Hoang (Ho Chi Minh City University of Technology - Vietnam National University Ho Chi Minh City, Vietnam)</li> <li>Tuan-Minh Pham (Phenikaa University, Vietnam)</li> <li>Umar Zakir Abdul Hamid (Sensible 4 Oy, Helsinki)</li> <li>Victor Leung (The University of British Columbia)</li> <li>Vo Nguyen Son Dr. (Duy Tan University, Vietnam)</li> <li>Wai-Wa Fung (Information Security and Forensics Society, Hong Kong)</li> <li>Walid Gaaloul (Institut National des Télécommunications, France)</li> <li>Weiwei Jiang, (Beijing University of Posts and Telecommunications (BUPT), China)</li> <li>Wendy W. Y. Hui (University of Nottingham at Ningbo, China)</li> <li>William Cheung (Hong Kong Baptist University, Hong Kong)</li> <li>Xianfu Chen (VTT Technical Research Centre of Finland, Finland)</li> <li>Xiang Gui (Massey University, New Zealand)</li> <li>Xiaoling Wu (Chinese Academy of Sciences, China)</li> <li>Xu Wang (Heriot Watt University, UK)</li> <li>Yan Bai (University of Washington Tacoma, USA)</li> <li>Yan Zhang (Simula Research Laboratory and University of Oslo, Norway)</li> <li>Yi Zhuang (Zhejian Gongshang University, China)</li> <li>Yong Li (Tsinghua University, China)</li> <li>Yong Tang (South China Normal University, China)</li> <li>Yuanfang Chen (Institute Mines-Telecom, University Pierre and Marie Curie )</li> <li>Yuexing Peng (Beijing University of Posts and Telecommunications, China)</li> <li>Yuqing Sun (Shangdong University, China)</li> <li>Zakaria Maamar (Zayed University, UAE)</li> <li>Zhangbing Zhou (China University of Geosciences, China)</li> <li>Zhichao Sheng (Shanghai University, China)</li> <li>ZhiMing Cai (Macau University of Science and Technology, Macau)</li> <li>Mithun Mukherjee (Nanjing University of Information Science and Technology, China)</li> <li> </li> </ul></div> <span class="expander more"><a class="trigger">more »</a></span></div><h2>Journal Blurb</h2><div class="abstract"><div class="shortened"><p>Visit the new journal website to submit and consult our contents: https://publications.eai.eu/index.php/inis/index</p></div><div class="full"><p>Visit the new journal website to submit and consult our contents: https://publications.eai.eu/index.php/inis/index</p></div> <span class="expander more"><a class="trigger">more »</a></span></div></div></div></section><section class="publication-info"><dl class="metadata"><dt class="title">Publisher</dt> <dd class="value">EAI</dd> <dt class="title">ISSN</dt> <dd class="value">2410-0218</dd> <dt class="title">Volume</dt> <dd class="value">6</dd></dl><dl class="metadata"><dt class="title">Published</dt> <dd class="value">2019-10-24</dd></dl></section></section></form></section></section><div class="clear"></div><footer><div class="links"><a href="https://www.ebsco.com/" target="_blank"><img class="logo ebsco-logo" src="/images/ebsco.png" alt="EBSCO"></a><a href="https://www.proquest.com/" target="_blank"><img class="logo proquest-logo" src="/images/proquest.png" alt="ProQuest"></a><a href="https://dblp.uni-trier.de/db/journals/publ/icst.html" target="_blank"><img class="logo dblp-logo" src="/images/dblp.png" alt="DBLP"></a><a 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