EAI Endorsed Transactions on Industrial Networks and Intelligent Systems

EAI Endorsed Transactions on Industrial Networks and Intelligent Systems is an open access, peer-reviewed scholarly journal focused on ubiquitous computing, cloud computing, and cyber-physical system, all kinds of networks in large-scale factories, including a lot of traditional and new industries. The journal, which is jointly sponsored and co-organized by Duy Tan University (Vietnam), publishes research articles, review articles, commentaries, editorials, technical articles, and short communications with a quarterly frequency. Authors are not charged for article submission and processing.

Editor(s)-in-Chief: Trung Q. Duong and Le Nguyen Bao

Aims & Scope
Indexing
Editors in Chief
Editorial Board
Special Issues

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.

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.
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.)
Analysis of industrial control and communication networks, including network lifetime, security, network scalability, reliability, stability, etc.
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
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.
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.
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.
Novel control techniques, with respect to process control, equipment control, supervisory control, adaptive control, motion control, etc.
Automated manufacturing systems, regarding formal modeling and analysis of manufacturing systems, scheduling of manufacturing systems, queuing systems and petri nets in manufacturing systems, etc.
Computational intelligence in automation, including neural, fuzzy, evolutionary approaches in automation, ant colonies optimization and swarm intelligence in automation, machine learning, expert systems, etc.
Hardware and software design and development for intelligent systems, such as intelligent and humanized production monitoring and control, etc.
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.
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.
Simulation and testbed of current industrial networks and intelligent systems, including network performance analysis, automated manufacturing, intelligent monitoring, disaster prevention, etc.
Vision of future smart factories, service, marketing, and their integration, incorporating current existing technologies.
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.
Pattern recognition methods for various industries and services: including statistical theory, clustering, similarity measures, unsupervised learning, supervised learning, etc.
Survey, review and essay of current industrial networks researches and intelligent systems development.

Call for Papers: Special issue on: General Collective Intelligence (Manuscript submission deadline: 2021-01-30; Notification of acceptance: 2021-03-01; Submission of final revised paper: 2021-03-31; Publication of special issue (tentative): 2021-04-16)

Lead Guest Editor: Andy E. Williams (Nobeah Foundation, Kenya)

Ala Al-Fuqaha (Western Michigan University, USA)
Al-Sakib Khan Pathan (Southeast University, Bangladesh)
Ammar Rayes (Cisco Systems, USA)
Antonino Masaracchia (IIT-CNR, Italy)
Athanasios Maglaras (Dr, Prof . ofT.E.I. of Larissa)
Ayse Kortun (Queen's University Belfast, UK)
Berk Canberk (Northeastern University, USA)
Ca V. Phan (Ho Chi Minh City University of Technology and Education, Vietnam)
Chau Yuen (Singapore University of Technology and Design, Singapore)
Chengfei Liu (Swinburne University of Technology, Australia)
Chinmoy Kundu (University of Texas at Dallas, USA)
Christer Carlsson (Åbo Akademi University, Finland)
Chunsheng Zhu (University of British Columbia)
Constandinos Mavromoustakis (University of Nicosia, Cyprus)
Der-Jiunn Deng (National Changhua University of Education, Taiwan)
Dickson Chiu (The University of Hong Kong)
Doan Xuan Toan (Thu Dau Mot University, Vietnam)
Eleanna Kafeza (Athens University of Economics and Business, Greece)
Fu-ren Lin (National Tsing Hua University, Taiwan)
Gerhard Hancke (University of London, UK)
Guangjie Han (Hohai University, China)
Guojun Wang (Central South University, China)
Hacene Fouchal (University of Reims Champagne-Ardenne, France)
Haklae Kim (Chung-Ang University, South Korea)
Halil Yetgin (Bitlis Eren University, Turkey)
Hideyasu Sasaki (Ritsumeikan University, Kyoto, Japan)
Ho-fung Leung (Chinese University of Hong Kong, Hong Kong)
Honggang Wang (University of Massachusetts Dartmouth, USA)
Hua Hu (Hangzhou Dianzi University, China)
Huy T. Nguyen (Inje University, South Korea)
Ibrahim Kushchu (Mobile Government Consortium International, UK)
Irene Kafeza (Irene Law Office, Greece)
Isabelle Comyn-Wattiau (ESSEC Business School Paris, France)
Jaime Lloret- Mauri (Universitat Politècnica de València, Spain)
Javier M. Aguiar (Universidad de Valladolid, Valladolid, Spain)
Jesus Alonso-Zarate (Telecommunications Technology Center of Catalonia, Spain)
Jian Yang (Macquarie University, Australia)
Jiankun Hu (University of New South Wales, Australia)
Jianmin Jiang (Shenzhen University)
Jianwei Niu (Beihang University, China)
Jinlei Jiang (Tsinghua University, China)
Jinsong Wu (Bell Laboratory, China)
Joel Rodrigues (Inst. Telecomunicações, Univ. of Beira Interior, Portugal)
Juan Trujillo (University of Alicante, Spain)
Jucheng Yang (Tianjing University of Technology, China)
Junqing Zhang (Queen's University Belfast)
KUN WANG (Nanjing University of Posts and Telecommunications)
Kuo-Ming Chao (Leader – Distributed Systems and Modelling Research Group, UK)
Leandros A. Maglaras (De Montfort University, UK)
Lei Wang (Dalian University of Technology, China)
Liang Zhou (Nanjing University of Posts and Telecommunications, China)
Long D. Nguyen (Dong Nai University, Vietnam)
Maggie M. Wang (The University of Hong Kong, Hong Kong)
Malcolm Egan (INSA Lyon)
Marijn Janssen (Delft University of Technology, The Netherlands)
Nicholas C Romano (Oklahoma State University, USA)
Noel Crespi (Institut Mines-Telecom, Telecom SudParis, France)
Panlong Yang (PLA University of Science and Technology, China)
Pasi Tyrväinen (University of Jyväskylä, Finland)
Patrick C.K. Hung (University of Ontario Institute of Technology, Canada)
Periklis Chatzimisios (Alexander TEI of Thessaloniki, Greece)
Phong Nam Nguyen (Memorial University of Newfoundland, Canada)
Pierluigi Siano (Università degli Studi di Salerno, Italy)
Pirkko Walden (Abo Akademi University, Finland)
Raymond Y.K Lau (City University of Hong Kong, Hong Kong)
Richard Yu (Carleton University, Canada)
Rong Yu (Guangdong University of Technology, China)
Rose Hu (Utah State University, USA)
Sammy Chan (City University of HongKong, HK)
Shing-Chi Cheung (Hong Kong University of Science and Technology, Hong Kong)
Stephen J. H. Yang (National Central University, Taiwan)
Syed Hassan Ahmed (University of Central Florida, USA)
Tran Trung Duy (PTIT, VietNam)
Trung Q. Duong (Blekinge Institute of Technology, Sweden)
Umar Zakir Abdul Hamid (Sensible 4 Oy, Helsinki)
Victor Leung (The University of British Columbia)
Vo Nguyen Son Dr. (Duy Tan University, Vietnam)
Wai-Wa Fung (Information Security and Forensics Society, Hong Kong)
Walid Gaaloul (Institut National des Télécommunications, France)
Wendy W. Y. Hui (University of Nottingham at Ningbo, China)
William Cheung (Hong Kong Baptist University, Hong Kong)
Xianfu Chen (VTT Technical Research Centre of Finland, Finland)
Xiang Gui (Massey University, New Zealand)
Xiaoling Wu (Chinese Academy of Sciences, China)
Xu Wang (Heriot Watt University, UK)
Yan Bai (University of Washington Tacoma, USA)
Yan Zhang (Simula Research Laboratory and University of Oslo, Norway)
Yi Zhuang (Zhejian Gongshang University, China)
Yong Li (Tsinghua University, China)
Yong Tang (South China Normal University, China)
Yuanfang Chen (Institute Mines-Telecom, University Pierre and Marie Curie )
Yuexing Peng (Beijing University of Posts and Telecommunications, China)
Yuqing Sun (Shangdong University, China)
Zakaria Maamar (Zayed University, UAE)
Zhangbing Zhou (China University of Geosciences, China)
ZhiMing Cai (Macau University of Science and Technology, Macau)
Zhiqiang Huo (GDUPT,UoL)
Mithun Mukherjee (Nanjing University of Information Science and Technology, China)
Zichao Sheng (ZTE, China)

Trung Q. Duong¹

Dr. Trung Q. Duong is a Reader at Queen’s University Belfast, U.K. His current research interests include IoT (applied to disaster management, agriculture, hydrometeorological hazards, smart grid) 5G networks (small-cell networks, ultra-dense networks, HetNets, physical layer security, massive MIMO, cell-free massive MIMO, caching, energy-harvesting), and nanoscale, molecular communications networks. He has authored or co-authored over 110 IEEE Journals. He is currently serving as an Editor for IEEE Trans on Wireless Communications, IEEE Trans on Communications, IET Communications and a Lead Senior Editor for IEEE Communications Letters. He has served as the Guest Editor for more than 22 times on ISI-index journals including the IEEE Journal in Selected Areas on Communications 2015, IET Communications 2014, 2016, 2017, IEEE Communications Magazine 2014 and 2015, IEEE Access 2016, 2017, 2018, IEEE Wireless Communications Magazine 2015, EURASIP JWCN, EURASIP JASP. He was an Editor of Electronics Letters, Emerging Telecommunications Technologies, IEEE Communications Letters. He has served as a chair for more than 20 IEEE conferences/workshops including the IEEE GLOBECOM 2016 Symposium Chair. Dr. Duong was awarded the Best Paper Award at the IEEE Vehicular Technology Conference (VTC-Spring) in 2013, the IEEE International Conference on Communications (ICC) 2014, the IEEE Global Communications Conference (GLOBECOM) 2016, IEEE Digital Signal Processing (DSP) 2017. He is a recipient of prestigious Royal Academy of Engineering Research Fellowship from 2016 to 2021 and has won the prestigious Newton Prize 2017.

Le Nguyen Bao²

Dr. Le Nguyen Bao is the Vice Provost and Head of the Technology & Science division as well as the R&D Center of Duy Tan University (DTU), which is widely considered to be the No. 1 private university in Vietnam. He earned his doctorate degree in Computer Science also from DTU, specializing in the field of facial recognition. His research interest is in network security policy, data warehousing, and 3D animation design. He helped initiate the CDIO (Conceive-Design-Implement-Operate) framework for engineering education first time in Central Vietnam back in 2010. His efforts ultimately led to the championship of Vietnamese students at the CDIO Academy, organized at Harvard and MIT in 2013. In 2017, he and his team again won the prestigious award for Vietnamese No. 1 Talents in Information Technology (IT) & Entrepreneurship for a 3D human-anatomy simulation. Under his leadership, Duy Tan University is aiming to become the top university for IT in Vietnam.

1: Queen's University Belfast, UK
2: Duy Tan University, Vietnam

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Intercept Probability Analysis of Cooperative Cognitive Networks Using Fountain Codes and Cooperative Jamming
Appears in:
inis 18: e3

Authors:
Tran Trung Duy, Le Chu Khan, Nguyen Thanh Binh, Nguyen Luong Nhat

Published:
26th Jan 2021

Abstract:
This paper evaluates intercept probability (IP) of a cooperative cognitive radio network. Using Fountain codes, a secondary source continuously generates encoded packets, and sends them to secondary destination and relay nodes that attempt to receive a sufficient number of the encoded p…This paper evaluates intercept probability (IP) of a cooperative cognitive radio network. Using Fountain codes, a secondary source continuously generates encoded packets, and sends them to secondary destination and relay nodes that attempt to receive a sufficient number of the encoded packets for recovering the source data. If the relay can sufficiently collect the packets before the destination, it replaces the source to transmit the encoded packets to the destination. Also in the secondary network, a passive eavesdropper attempts to illegally receive the packets sent by the source and relay nodes, and if it can accumulate enough encoded packets, the source data is intercepted. To enhance secrecy performance, in terms of IP, a cooperative jammer is used to transmit noises on the eavesdropper. We also propose a simple transmit power allocation method for the secondary transmitters such as source, relay and jammer so that outage performance of a primary network is not harmful. We derive an exact closed-form expression of IP over Rayleigh fading channel, and verify it by performing Monte-Carlo simulations.
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Design of Group Precoding for MU-MIMO Systems with Exponential Spatial Correlation Channel
Appears in:
inis 18: e2

Authors:
Van-Khoi Dinh, Thanh-Binh Chu, Minh-Tuan Le, Vu-Duc Ngo

Published:
26th Jan 2021

Abstract:
In this paper, a low-complexity precoding algorithm is proposed to reduce the computational complexity and improve the performance for MU-MIMO systems under exponential spatial correlation channel conditions. The proposed precoders are designed consisting of two components: The first one mi…In this paper, a low-complexity precoding algorithm is proposed to reduce the computational complexity and improve the performance for MU-MIMO systems under exponential spatial correlation channel conditions. The proposed precoders are designed consisting of two components: The first one minimizes the interference among neighboring user groups, while the second one improves the system performance. Numerical and simulation results show that the proposed precoders have remarkably lower computational complexities than their existing LC-RBD-LR-ZF and BD counterparts. Besides, BER performances of the proposed precoders are asymptotic to that of LC-RBD-LR-ZF precoder at the low SNR region and better than that of LC-RBD-LR-ZF precoder at the high SNR region. Simulation results also show that the performance of the proposed algorithms is significantly improved compared to the BD algorithm in an exponential spatial correlation channel.
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An Efficient Pest Classification In Smart Agriculture Using Transfer Learning
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inis 18: e1

Authors:
Tuan T. Nguyen, Quoc-Tuan Vien, Harin Sellahewa

Published:
26th Jan 2021

Abstract:
To this day, agriculture still remains very important and plays considerable role to support our daily life and economy in most countries. It is the source of not only food supply, but also providing raw materials for other industries, e.g. plastic, fuel. Currently, farmers are faci…To this day, agriculture still remains very important and plays considerable role to support our daily life and economy in most countries. It is the source of not only food supply, but also providing raw materials for other industries, e.g. plastic, fuel. Currently, farmers are facing the challenge to produce sufficient crops for expanding human population and growing in economy, while maintaining the quality of agriculture products. Pest invasions, however, are a big threat to the growth crops which cause the crop loss and economic consequences. If they are left untreated even in a small area, they can quickly spread out other healthy area or nearby countries. A pest control is therefore crucial to reduce the crop loss. In this paper, we introduce an efficient method basing on deep learning approach to classify pests from images captured from the crops. The proposed method is implemented on various EfficientNet and shown to achieve a considerably high accuracy in a complex dataset, but only a few iterations are required in the training process.
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User mobility into NOMA assisted communication: Analysis and a Reinforcement Learning with Neural Network based approach
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inis 21(25): e5

Authors:
Antonino Masaracchia, Minh T. Nguyen, Ayse Kortun

Published:
7th Jan 2021

Abstract:
This article proposes a performance analysis of a non-orthogonal multiple access (NOMA) transmission system in the presence of user mobility. The main objective is to illustrate how the users’ mobility can affect the system performance in terms of downlink aggregated th…This article proposes a performance analysis of a non-orthogonal multiple access (NOMA) transmission system in the presence of user mobility. The main objective is to illustrate how the users’ mobility can affect the system performance in terms of downlink aggregated throughput, downlink network fairness, and percentage of quality-of-service requirement guaranteed. The idea behind is to highlight the importance to take into account user mobility in designing power allocation policies for NOMA systems. It is shown how the communication technologies are mainly dependent from channel state information (CSI) which in turns depends on users’ mobility. In addition a reinforcement learning (RL) to tackle with user mobility is proposed. Performance investigations regarding the proposed framework have shown how the network performances inpresence of users’ mobility can be improved, especially when a feed-forward neural network is used as CSI estimator.
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Structural Importance-based Link Prediction Techniques in Social Network
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inis 21(25): e4

Authors:
Abdul Samad, Muhammad Azam, Mamoona Qadir

Published:
7th Jan 2021

Abstract:
Link prediction in social network gaining high attention of researchers nowadays due to the rush of users towards social network. Link prediction is known as the prediction of missing or unobserved link, i.e., new interaction is going to be occurring in a near future. Stat…Link prediction in social network gaining high attention of researchers nowadays due to the rush of users towards social network. Link prediction is known as the prediction of missing or unobserved link, i.e., new interaction is going to be occurring in a near future. State-of-the-art link prediction techniques (e.g., Jaccard Index, Resource Allocation, SAM Similarity, Sorensen Index, Salton Cosine, Hub Depressed Index and Parameter-Dependent) considers only similarity of the pair of node in order to find the link. However, we argued that nodes having same status of centralization along with high similarity can connect to each other in a future. In this paper, we have proposed structural importance-based state-of-the-art link prediction techniques and compared. We have compared structural importance-based link prediction techniques with state-of-the-art techniques. The experiments are performed on four different datasets (i.e., Astro, CondMat, HepPh and HepTh). Our results show that structural importance-based link prediction techniques outperformed than state-of-the-art link prediction techniques by getting 95% at threshold 0.1 and 68% at threshold 0.7.
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D2D Multi-hop Multi-path Communications in B5G Networks: A Survey on Models, Techniques, and Applications
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inis 21(25): e3

Authors:
Quang-Nhat Tran, Nguyen-Son Vo, Quynh-Anh Nguyen, Minh-Phung Bui, Thanh-Minh Phan, Van-Viet Lam, Antonino Masaracchia

Published:
7th Jan 2021

Abstract:
In 5G networks, device-to-device (D2D) communications have played an important role in enlarging the coverage, relaxing the workload of backhaul links of both macro base stations (MBSs) and small-cell basestations (SBSs), and serving the mobile users (MUs) local applications and servic…In 5G networks, device-to-device (D2D) communications have played an important role in enlarging the coverage, relaxing the workload of backhaul links of both macro base stations (MBSs) and small-cell basestations (SBSs), and serving the mobile users (MUs) local applications and services at high capacity. However, beyond 5G (B5G or 6G) networks will require disruptive solutions that can assist D2D communications to meet numerous advanced applications and services requested by dense MUs. One of the most efficient solutions for D2D communications is multi-hop multi-path (MHMP). In this paper, we present a detailed survey of the so called D2D MHMP communications in terms of models, techniques, and applications for B5Gnetworks. We discuss and propose the future research directions of D2D MHMP communications. All themodels, techniques, and applications as well as future research directions of D2D MHMP communications provide the useful insights into B5G networks design and optimisation.
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Real-time Optimisation for Industrial Internet of Things (IIoT): Overview, Challenges and Opportunities
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inis 21(25): e2

Authors:
Long D. Nguyen, Ayse Kortun

Published:
16th Dec 2020

Abstract:
Industrial Internet-of-Things (IIoT) with massive data transfers and huge numbers of connected devices, incombination with the high demand for greater quality-of-services, signal processing is no longer producing small data sets but rather, very large ones (measured in gigabytes or tera…Industrial Internet-of-Things (IIoT) with massive data transfers and huge numbers of connected devices, incombination with the high demand for greater quality-of-services, signal processing is no longer producing small data sets but rather, very large ones (measured in gigabytes or terabytes), or even higher. This has posed critical challenges in the context of optimisation. Communication scenarios such as online applications come with the need for real-time optimisation. In such scenarios, often under a dynamic environment, a strict real-time deadline is the most important requirement to be met. To this end, embedded convex optimisation, which can be redesigned and updated within a fast time-scale given sufficient computing power, is a candidate to deal with the challenges in real-time optimisation applications. Real-time optimisation is now becoming a reality in signal processing and wireless networks of IIoT. Research into new technologies to meet future demands is receiving urgent attention on a global scale, especially when 5G networks are expected to be in place in 2020. This work addresses the fundamentals, technologies and practically relevant questions related to the many challenges arising from real-time optimisation communications for industrial IoT.
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Optimizing the Modified Lam Annealing Schedule
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inis 21(25): e1

Author:
Vincent A. Cicirello

Published:
16th Dec 2020

Abstract:
Simulated annealing is a metaheuristic commonly used for combinatorial optimization in many industrial applications. Its runtime behavior is controlled by an algorithmic component known as the annealing schedule. The classic annealing schedules have control parameters that must be set …Simulated annealing is a metaheuristic commonly used for combinatorial optimization in many industrial applications. Its runtime behavior is controlled by an algorithmic component known as the annealing schedule. The classic annealing schedules have control parameters that must be set or tuned ahead of time. Adaptive annealing schedules, such as the Modified Lam, are parameter-free and self-adapt during runtime. However, they are also more complex than the classic alternatives, leading to more time per iteration. In this paper, we present an optimized variant of Modified Lam annealing, and experimentally demonstrate the potential significant impact on runtime performance of carefully optimizing the annealing schedule.
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The impact of user mobility into non-orthogonal multiple access (NOMA) transmission systems
Appears in:
inis 20(24): e5

Authors:
Antonino Masaracchia, Van-Long Nguyen, Minh T. Nguyen

Published:
21st Oct 2020

Abstract:
Non-orthogonal multiple access techniques (NOMA) have been recognized as a paradigm shift for the design of multiple access techniques for the next generation of wireless networks. Many existing works on NOMA have focused on scenarios with low-mobility users (static), where users with di…Non-orthogonal multiple access techniques (NOMA) have been recognized as a paradigm shift for the design of multiple access techniques for the next generation of wireless networks. Many existing works on NOMA have focused on scenarios with low-mobility users (static), where users with different channel conditionsor quality of service (QoS) requirements are grouped together for the implementation of NOMA. However, when increased, user mobility can strongly impacts on the performance of a NOMA systems, especially in the context of downlink perceived throughput, networ fairness and QoS fuilfilment of each users. This paper presents some of the main drawback which can be obtained if the user mobility is not taken into account inthe design of NOMA communication systems. Future direction and challenges to address these issues are also discussed.
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Toward Understanding the Interplay between Public and Private Healthcare Providers and Patients: An Agent-based Simulation Approach
Appears in:
inis 20(24): e4

Authors:
Zainab Alalawi, Yifeng Zeng, The Anh Han

Published:
21st Oct 2020

Abstract:
Few modelling studies have been carried out to investigate patients’ involvement in the decision-making process in a healthcare system. Here we perform theoretical and simulation analysis of a healthcare business model involving three populations: Public Healthcare Providers, Private Healthcare Pro…Few modelling studies have been carried out to investigate patients’ involvement in the decision-making process in a healthcare system. Here we perform theoretical and simulation analysis of a healthcare business model involving three populations: Public Healthcare Providers, Private Healthcare Providers and Patients. The analysis contributes to healthcare economic modelling by analyzing the dynamics and emergence of cooperative behavior of agents within the three populations. Resorting to agent-based simulations, we examine the effect of increasing behavioural mutation and providers’ capacity on patients’ cooperative behaviour. We show that the former introduces more randomness in agents’ behaviors enabling cooperation to emerge in more difficult conditions. Moreover, when the providers’ capacity to meet patients’ demand is limited, patients exhibit low levels of cooperation, implying a more difficult cooperation dilemma in a healthcare system that needs addressing.
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Synapse. A Neutron Spectrum Unfolding Code Based on Generalized Regression Artificial Neural Networks
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inis 20(24): e3

Authors:
Ma. del Rosario Martinez-Blanco, Arturo Serrano-Muñoz, Hector Rene Vega-Carrillo, Marco Aurelio de Sousa-Lacerda, Roberto Mendez-Villafañe, Eduardo Gallego, Antonio del Rio de Santiago, Luis Octavio Solis-Sanchez, Jose Manuel Ortiz-Rodriguez

Published:
21st Oct 2020

Abstract:
In its broadest sense, the term artificial intelligence indicates the ability of an artifact to perform the same types of functions that characterize human thought. The goal of AI is to use algorithms, heuristics and methodologies based on the ways in which the human brain …In its broadest sense, the term artificial intelligence indicates the ability of an artifact to perform the same types of functions that characterize human thought. The goal of AI is to use algorithms, heuristics and methodologies based on the ways in which the human brain solves problems. Artificial neural networks recreate the structure of the human brain imitating the learning process. The Artificial neural networks theory has provided an alternative to classical computing for those problems in which traditional methods have delivered results that are not very convincing or not very convenient such as in the case of the neutron spectrometry and dosimetry problem for radiation protection purposes, using the Bonner spheres spectrometer as measurement system, mainly because many problems are encountered when trying to determine the neutron energy spectrum of a measured data. The most delicate part of the spectrometry based on this system is the unfolding process, for which several neutron spectrum unfolding codes have being developed. However, these codes require an initial guess spectrum in order to initiate the unfolding process. Their poor availability and their not easy management for the end user are other associated problems. Artificial Intelligence technology, is an alternative technique that is gaining popularity among researchers in neutron spectrometry research area, since it offers better results compared with the traditional solution methods. In this work, "Synapse", a neutron spectrum unfolding code based on Generalized Regression Artificial Neural Networks technology is presented. The Synapse code is capable to unfold the neutron spectrum and to calculate 15 dosimetric quantities using the count rates, coming from a BSS as the only entrance information. The results obtained show that the Synapse code, based on GRANN technology, is a promising and innovative technological alternative for solving the neutron spectrometry and dosimetry problems.
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An Efficient DCT-SVD Steganographic Approach Applied to JPEG Images
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inis 20(24): e2

Authors:
Franklin Tchakounté, Priva Chassem Kamdem, Jean Claude Kamgang, Hortense Boudjou Tchapgnouo, Marcellin Atemkeng

Published:
28th Sep 2020

Abstract:
To prove the origin of images in social media, this work proposes an efficient JPEG image steganography approach. After structuring the cover image into blocks of 8*8 pixels, Discrete Cosine Transform is applied to each block of pixels. The latter are quantified using a quantization…To prove the origin of images in social media, this work proposes an efficient JPEG image steganography approach. After structuring the cover image into blocks of 8*8 pixels, Discrete Cosine Transform is applied to each block of pixels. The latter are quantified using a quantization table and a matrix of DC coefficients from quantized blocks of pixels, is obtained. Singular Value Decomposition is applied to the previous matrix and the secret message is inserted within singular vectors. For extraction purposes, previous transformations are followed reversely. An experimentation is made on seven images and results show that the proposed system outperforms similar studies in three aspects (i) it preserves stego image quality with PSNR of stego images varying between 38 and 54 (ii) it is able to insert a secret message of 257600 bits with the capacity of 4 bits per pixel (iii) it is robust and resistant to attacks such as histogram analysis and chi-square test.
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Correlation Analysis of Vital Signs to Monitor Disease Risks in Ubiquitous Healthcare System
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inis 20(24): e1

Authors:
Hassan Murtaza, Muhammad Azhar Iqbal, Qammer H. Abbasi, Sajjad Hussain, Huanlai Xing, Muhammad A. Imran

Published:
27th Jul 2020

Abstract:
Healthcare systems for chronic diseases demand continuous monitoring of physiological parameters or vital signs of the patients’ body. Through these vital signs’ information, healthcare experts attempt to diagnose the behavior of a disease. Identifying the relationship between these vital signs i…Healthcare systems for chronic diseases demand continuous monitoring of physiological parameters or vital
signs of the patients’ body. Through these vital signs’ information, healthcare experts attempt to diagnose
the behavior of a disease. Identifying the relationship between these vital signs is still a big question for the
research community. We have proposed a sophisticated way to identify the affiliations between vital signs
of three specific diseases i.e., Sepsis, Sleep Apnea, and Intradialytic Hypotension (IDH) through Pearson
statistical correlation analysis. Vital signs data of about 32 patients were taken for analysis. Experimental
results show significant affiliations of vital signs of Sepsis and IDH with average correlation coefficient of 0.9
and 0.58, respectively. The stability of the mentioned correlation is about 75% and 90%, respectively.
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Smart Grid Attacks and Countermeasures
Appears in:
inis 15(2): e4

Authors:
Eric McCary, Yang Xiao

Downloads:
1890

Abstract:
The term “Smart Grid” has been coined and used for several years to describe the efforts of the current power grid modernization effort. This effort plans to introduce self-healing, energy efficiency, reliability, and security using two-way digital communications and control technology, along with …The term “Smart Grid” has been coined and used for several years to describe the efforts of the current power grid modernization effort. This effort plans to introduce self-healing, energy efficiency, reliability, and security using two-way digital communications and control technology, along with a host of other valuable attributes. As a bi-product of this modernization and newly gained systems interoperability, new communications and management interfaces are produced in both the cyber realm and physical domains. The increase of the public physical presence and cyber footprint opens up avenues for compromise to hackers and individuals with malicious intent. This survey paper will categorize and summarize vulnerabilities in the framework of the current power grid and the software and hardware which is currently being used to upgrade the grid. The paper will also detail known countermeasures which can be used to mitigate or eliminate attacks which exploit such vulnerabilities.
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Innovative Application of 5G and Blockchain Technology in Industry 4.0
Appears in:
inis 19(18): e4

Authors:
Ivan Jovović, Siniša Husnjak, Ivan Forenbacher, Sven Maček

Downloads:
1346

Abstract:
The Industry 4.0 is experiencing significant challenges, including the need for an increased amount of data transmission with improved security, transparency and credibility. The 5th Generation Mobile Network (5G) and Blockchain are innovative emerging technologies that can respond to these needs. …The Industry 4.0 is experiencing significant challenges, including the need for an increased amount of data transmission with improved security, transparency and credibility. The 5th Generation Mobile Network (5G) and Blockchain are innovative emerging technologies that can respond to these needs. 5G will enable extremely large channel capacities and reduce data latency, while Blockchain's innovative data-sharing mode of operation delivers an improved high level of security, transparency, and credibility of stored data. Therefore, this paper presents a general survey of the potential application of 5G network and Blockchain technology in Industry 4.0. The results may be used by first-movers firms for gaining technological leadership on the market.
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A Survey of System Level Power Management Schemes in the Dark-Silicon Era for Many-Core Architectures
Appears in:
inis 18(15): e5

Authors:
Emmannuel Ofori-Attah, Xiaohang Wang, Michael Opoku Agyeman

Downloads:
1253

Abstract:
Power consumption in Complementary Metal Oxide Semiconductor (CMOS) technology has escalated to a point that only a fractional part of many-core chips can be powered-on at a time. Fortunately, this fraction can be increased at the expense of performance through the dark-silicon solution. However, w…Power consumption in Complementary Metal Oxide Semiconductor (CMOS) technology has escalated to a point that only a fractional part of many-core chips can be powered-on at a time. Fortunately, this fraction can be increased at the expense of performance through the dark-silicon solution. However, with many-core integration set to be heading towards its thousands, power consumption and temperature increases per time, meaning the number of active nodes must be reduced drastically. Therefore, optimized techniques are demanded for continuous advancement in technology. Existing eﬀorts try to overcome this challenge by activating nodes from diﬀerent parts of the chip at the expense of communication latency. Other eﬀorts on the other hand employ run-time power management techniques to manage the power performance of the cores trading-oﬀ performance for power. We found out that, for a signiﬁcant amount of power to saved and high temperature to be avoided, focus should be on reducing the power consumption of all the on-chip components. Especially, the memory hierarchy and the interconnect. Power consumption can be minimized by, reducing the size of high leakage power dissipating elements, turning-oﬀ idle resources and integrating power saving materials.
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An Introduction of Real-time Embedded Optimisation Programming for UAV Systems under Disaster Communication
Appears in:
inis 18(17): e5

Authors:
Long D. Nguyen, Ayse Kortun, Trung Q. Duong

Downloads:
998

Abstract:
For disaster communications, it is very challenging for the contemporary wireless technology and infrastructure to meet the demands for connectivity. Modern wireless networks should be developed to satisfy the increasing demand of quality-of-service (QoS) in mission-critical communications for disa…For disaster communications, it is very challenging for the contemporary wireless technology and infrastructure to meet the demands for connectivity. Modern wireless networks should be developed to satisfy the increasing demand of quality-of-service (QoS) in mission-critical communications for disaster management which are currently faced with the challenges of limited spectrum, expensive resources, reliable and green communication. There is a tremendous need for optimisation techniques in the study and design of the key functionalities of wireless systems. Until now, almost current optimisation scenarios are often carried out on large timescales (e.g., minutes or hours) without strict time constraints for solving the problems. With the improvement of computational speed, eﬃcient algorithms and advanced coding approaches, a framwork of real-time optimisation programming, which plays a major role in the trend of modern engineering such as mission-critical communications, is introduced for the first time in this paper in the context of natural disaster. In particular, we propose an introduction of embedded convex optimisation programming for unmanned ariel vehicles (UAVs) communications in disaster networks with the strict supervision of executive time in real-time scenarios.
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Improving ns-3 Emulation Support in Real-World Networking Scenarios
Appears in:
inis 16(9): e5

Authors:
Helder Fontes, Rui Campos, Manuel Ricardo

Downloads:
949

Abstract:
A common problem in networking research and development is the duplicate effort of writing simulation and implementation code. This duplication can be avoided through the use of fast-prototyping methodologies, which enable reusing simulation code in real prototyping and in production environments. …A common problem in networking research and development is the duplicate effort of writing simulation and implementation code. This duplication can be avoided through the use of fast-prototyping methodologies, which enable reusing simulation code in real prototyping and in production environments. Although this functionality is already available by using ns-3 emulation, there are still limitations regarding the support of real network interfaces and easy configuration of the network settings, such as IP and MAC addresses.
In this paper we propose an improved version of the ns-3 emulation component by introducing new functionalities that address these limitations. The new functionalities include the support of new types of real network interfaces and the easier integration of emulation nodes with existing networks by means of a new auto-configuration mechanism for ns-3 nodes. Experimental results obtained in a laboratorial testbed and in a real vehicular network testbed demonstrate the new functionalities proper operation, and their backwards compatibility with previously coded ns-3 scenarios.
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Attribution of Cyber Attacks on Industrial Control Systems
Appears in:
inis 16(7): e3

Authors:
Allan Cook, Andrew Nicholson, Helge Janicke, Leandros Maglaras, Richard Smith

Downloads:
947

Abstract:
In order to deter or prosecute for cyber attacks on industrial control systems it is necessary to assign attribution to the attacker and define the type of attack so that international law enforcement agencies or national governments can decide on appropriate recourse. In this paper we identify the…In order to deter or prosecute for cyber attacks on industrial control systems it is necessary to assign attribution to the attacker and define the type of attack so that international law enforcement agencies or national governments can decide on appropriate recourse. In this paper we identify the current state of the art of attribution in industrial control systems. We highlight the critical differences between attribution in enterprise networks and attribution in industrial networks. In doing so we provide a roadmap for future research.
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Design of Cloud-Connected IoT System for Smart Buildings on Energy Management (Invited paper)
Appears in:
inis 16(6): e3

Authors:
Wayes Tushar, Chau Yuen, Kai Li, Kristin L. Wood, Zhang Wei, Liu Xiang

Downloads:
921

Abstract:
Building energy management (BEM) system can provide cost-effective energy management solutions for smart buildings. However, the success of BEM is contingent on identifying large energy consuming devices, monitoring energy usage, optimal scheduling of flexible appliances, and distinguishing and con…Building energy management (BEM) system can provide cost-effective energy management solutions for smart buildings. However, the success of BEM is contingent on identifying large energy consuming devices, monitoring energy usage, optimal scheduling of flexible appliances, and distinguishing and controlling energy wastage. To this end, this paper discusses the design of Internet of Things (IoT) for a flexible BEM with the backend analytic that performs analysis on energy usage pattern and the wastage. We present the experimental results of real-time monitoring of consumers’ energy usage in a commercial space to identify the electricity wastage. The experiment is conducted at an office testbed using a comprehensive wireless sensor network. Extensive analysis is done to identify the energy wastage pattern of users for reducing the electricity cost. It is demonstrated that it is possible to reduce significant energy wastage when an office building is equipped with the proposed IoT system.
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Security Issues in ProtoGENI
Appears in:
inis 16(6): e1

Authors:
Fnu Shalini, Yang Xiao, Bo Sun

Downloads:
902

Abstract:
Network security consists of primary concerns in future Internet development due to the ever increasing threats to current Internet. ProtoGENI is a federated testbed facility supporting slice-based experiments to manage, utilize, and monitor the resources for innovative network research. Security…Network security consists of primary concerns in future Internet development due to the ever increasing threats to current
Internet. ProtoGENI is a federated testbed facility supporting slice-based experiments to manage, utilize, and monitor the
resources for innovative network research. Security research in ProtoGENI is crucial because experiments conducted in
manipulated or corruptted test environment can mislead about security mechanism’s capabilities in a system. In this paper,
existing ProtoGENI security mechanisms and functions are tested and analyzed through different experiments to find out
the exploitable attacking loopholes. Experiments elaborate the existing functioning and security issues that can cause nonfunctional,
semi non-functional or malfunctioned systems. Results indicate threats to ProtoGENI resources and run-time
interactions. Cross-experiment communication in Emulab wireless nodes have the capability of assisting in verifying
isolation between ProtoGENI slices. Host security is one of the security components, which can be enhanced by modifying
default security settings including SSH port number and root login rights. Documentation of experiment environment,
experiment design, results, and analysis including many observations is helpful to understand the basic functioning and
security issues to improve the overall functioning and security of ProtoGENI.
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Hardware-software co-simulation for medical X-ray control units
Appears in:
inis 16(8): e5

Authors:
Bruno Kleinert, Gholam Reza Rahimi, Marc Reichenbach, Dietmar Fey

Downloads:
869

Abstract:
In this paper we present our solution to master the complex- ity of product adaption cycles of a medical X-ray control unit. We present the real hardware and software platform and our mapping of it to a virtual X-ray control unit, im- plemented as our hardware-software co-simulation. To re- du…In this paper we present our solution to master the complex-
ity of product adaption cycles of a medical X-ray control
unit. We present the real hardware and software platform
and our mapping of it to a virtual X-ray control unit, im-
plemented as our hardware-software co-simulation. To re-
duce complexity for hardware developers, we developed our
own XML-based abstract system description language which
is mapped onto instantiations of parameterizable SystemC
template modules. We verified the correctness of our virtual
X-ray control unit by co-simulating unmodified software to
hardware components, which we implemented in our system
description language from the specification of the real sys-
tem. Due to reduced complexity of our virtual X-ray control
unit, it can be used as a time and cost saving test platform
for future hardware and software adaption cycles.
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An Investigation of Performance Analysis of Anomaly Detection Techniques for Big Data in SCADA Systems
Appears in:
inis 15(3): e5

Authors:
Mohiuddin Ahmed, Adnan Anwar, Abdun Naser Mahmood, Zubair Shah, Michael J. Maher

Downloads:
862

Abstract:
Anomaly detection is an important aspect of data mining, where the main objective is to identify anomalous or unusual data from a given dataset. However, there is no formal categorization of application-specific anomaly detection techniques for big data and this ignites a confusion for the data m…Anomaly detection is an important aspect of data mining, where the main objective is to identify anomalous
or unusual data from a given dataset. However, there is no formal categorization of application-specific
anomaly detection techniques for big data and this ignites a confusion for the data miners. In this paper, we
categorise anomaly detection techniques based on nearest neighbours, clustering and statistical approaches
and investigate the performance analysis of these techniques in critical infrastructure applications such as
SCADA systems. Extensive experimental analysis is conducted to compare representative algorithms from
each of the categories using seven benchmark datasets (both real and simulated) in SCADA systems. The
effectiveness of the representative algorithms is measured through a number of metrics. We highlighted the
set of algorithms that are the best performing for SCADA systems.
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Publisher: EAI
ISSN: 2410-0218
Number of Volumes: 7

Last Published: 2021-01-07

EAI Endorsed Transactions on Industrial Networks and Intelligent Systems

Trung Q. Duong1

Le Nguyen Bao2

Trung Q. Duong¹

Le Nguyen Bao²