EAI Endorsed Transactions on Industrial Networks and Intelligent Systems

Visit the new journal website to submit and consult our contents: https://publications.eai.eu/index.php/inis/index

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

Aims & Scope
Indexing
Editorial Board

EAI Endorsed Transactions on Industrial Networks and Intelligent Systems is open access, a 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 (four issues per year). Authors are not charged for article submission and processing.

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.

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)
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)
Mithun Mukherjee (Nanjing University of Information Science and Technology, China)
Zichao Sheng (ZTE, China)

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Human Activity Recognition System For Moderate Performance Microcontroller Using Accelerometer Data And Random Forest Algorithm
Appears in:
inis 22(4): e4

Authors:
To-Hieu Dao, Hai-Yen Hoang, Van-Nhat Hoang, Duc-Tan Tran, Duc-Nghia Tran

Published:
21st Dec 2022

Abstract:
There has been increasing interest in the application of artificial intelligence technologies to improve the quality of support services in healthcare. Some constraints, such as space, infrastructure, and environmental conditions, present challenges with assistive devices for humans. This paper pro…There has been increasing interest in the application of artificial intelligence technologies to improve the quality of support services in healthcare. Some constraints, such as space, infrastructure, and environmental conditions, present challenges with assistive devices for humans. This paper proposed a wearable-based real-time human activity recognition system to monitor daily activities. The classification was done directly on the device, and the results could be checked over the internet. The accelerometer data collection application was developed on the device with a sampling frequency of 20Hz, and the random forest algorithm was embedded in the hardware. To improve the accuracy of the recognition system, a feature vector of 31 dimensions was calculated and used as an input per time window. Besides, the dynamic window method applied by the proposed model allowed us to change the data sampling time (1-3 seconds) and increase the performance of activity classification. The experiment results showed that the proposed system could classify 13 activities with a high accuracy of 99.4%. The rate of correctly classified activities was 96.1%. This work is promising for healthcare because of the convenience and simplicity of wearables.
more »
Functional Security and Trust in Ultra-Connected 6G Ecosystem
Appears in:
inis 22(4): e5

Author:
Vishal Sharma

Published:
20th Dec 2022

Abstract:
Security and trust are the entangled role players in the future generation of wireless networks. Security in 5G networks is currently supported using several functions. Given the advantages of such a system, this article explores the functional security and trust for the 6G ecosystem with ultra-con…Security and trust are the entangled role players in the future generation of wireless networks. Security in 5G networks is currently supported using several functions. Given the advantages of such a system, this article explores the functional security and trust for the 6G ecosystem with ultra-connectivity. Several associated challenges, application-specific domains, and consumer issues related to 6G security are discussed. The article highlights the network security-by-design and trust-by-design principles and performance expectations from the security protocols in supporting handover in an ultra-connected scenario. Finally, potential research directions are presented for a road towards the 6G ecosystem.
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Phase Impairment Estimation for mmWave MIMO Systems with Low Resolutions ADC and Imperfect CSI
Appears in:
inis 22(4): e3

Authors:
Nguyen Dinh Ngoc, Kien Truong

Published:
28th Oct 2022

Abstract:
Multiple-Input Multiple-Output systems operating at millimeter wave band (mmWave MIMO) are a promising technology next generations of mobile networks. In practice, the non-ideal hardware is a challenge for commercially viable mmWave MIMO transceivers and come from non-linearities of the amplifier, …Multiple-Input Multiple-Output systems operating at millimeter wave band (mmWave MIMO) are a promising technology next generations of mobile networks. In practice, the non-ideal hardware is a challenge for commercially viable mmWave MIMO transceivers and come from non-linearities of the amplifier, phase noise, quantization errors, mutual coupling between antenna ports, and In-phase/Quadrature (I/Q) imbalance. As a result, the received signals are affected by non-ideal transceiver hardware components, thus reduce the performance of such systems, especially phase impairment caused by phase noise and carrier frequency offset (CFO). In this paper, we consider a mmWave MIMO system model that takes into account many practical hardware impairments and imperfect channel state information (CSI). Our main contributions are a problem formulation of phase impairments with imperfect CSI and a low-complexity estimation method to solve the problem. Numerical results are provided to evaluate the performance of the proposed algorithm.
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An Accurate Viewport Estimation Method for 360 Video Streaming using Deep Learning
Appears in:
inis 22(4): e2

Authors:
Hung Nguyen, Thu Ngan Dao, Ngoc Son Pham, Tran Long Dang, Trung Dung Nguyen, Thu Huong Truong

Published:
21st Sep 2022

Abstract:
Nowadays, Virtual Reality is becoming more and more popular, and 360 video is a very important part of the system. 360 video transmission over the Internet faces many difficulties due to its large size. Therefore, to reduce the network bandwidth requirement of 360-degree video, Viewport Adaptive St…Nowadays, Virtual Reality is becoming more and more popular, and 360 video is a very important part of the system. 360 video transmission over the Internet faces many difficulties due to its large size. Therefore, to reduce the network bandwidth requirement of 360-degree video, Viewport Adaptive Streaming (VAS) was proposed. An important issue in VAS is how to estimate future user viewing direction. In this paper, we propose an algorithm called GLVP (GRU-LSTM-based-Viewport-Prediction) to estimate the typical view for the VAS system. The results show that our method can improve viewport estimation from 9.5% to near 20%compared with other methods.
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Internet Traffic Prediction Using Recurrent Neural Networks
Appears in:
inis 22(4): e1

Authors:
Mircea Eugen Dodan, Quoc-Tuan Vien, Tuan Thanh Nguyen

Published:
2nd Sep 2022

Abstract:
Network traffic prediction (NTP) represents an essential component in planning large-scale networks which are in general unpredictable and must adapt to unforeseen circumstances. In small to medium-size networks, the administrator can anticipate the fluctuations in traffic without the need of using…Network traffic prediction (NTP) represents an essential component in planning large-scale networks which are in general unpredictable and must adapt to unforeseen circumstances. In small to medium-size networks, the administrator can anticipate the fluctuations in traffic without the need of using forecasting tools, but in the scenario of large-scale networks where hundreds of new users can be added in a matter of weeks, more efficient forecasting tools are required to avoid congestion and over provisioning. Network and hardware resources are however limited; and hence resource allocation is critical for the NTP with scalable solutions. To this end, in this paper, we propose an efficient NTP by optimizing recurrent neural networks (RNNs) to analyse the traffic patterns that occur inside flow time series, and predict future samples based on the history of the traffic that was used for training. The predicted traffic with the proposed RNNs is compared with the real values that are stored in the database in terms of mean squared error, mean absolute error and categorical cross entropy. Furthermore, the real traffic samples for NTP training are compared with those from other techniques such as auto-regressive moving average (ARIMA) and AdaBoost regressor to validate the effectiveness of the proposed method. It is shown that the proposed RNN achieves a better performance than both the ARIMA and AdaBoost regressor when more samples are employed.
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Intelligent Reflecting Surface assisted RF Energy Harvesting Mobile Edge Computing NOMA Networks: Performance Analysis and Optimization
Appears in:
inis 22(32): 5

Authors:
Dac-Binh Ha, Van-Truong Truong, Yoonill Lee

Published:
11th Aug 2022

Abstract:
In this paper, we focus on the performance analysis and optimization of an RF energy harvesting (EH) mobile edge computing (MEC) network by the assistance of the intelligent reflecting surface (IRS) and non-orthogonal multiple access (NOMA) schemes. Specifically, a pair of users harvest RF energy f…In this paper, we focus on the performance analysis and optimization of an RF energy harvesting (EH) mobile edge computing (MEC) network by the assistance of the intelligent reflecting surface (IRS) and non-orthogonal multiple access (NOMA) schemes. Specifically, a pair of users harvest RF energy from a hybrid access point (HAP) and offloads their tasks to the MEC server at HAP through wireless links by employing an IRS-aided and uplink NOMA scheme. To evaluate the performance of this proposed system, the closed-form expressions of successful computation and energy transfer efficiency probabilities are derived. We further formulate a multi-objective optimization problem and propose an algorithm to find the optimal energy harvesting time switching ratio value to achieve the best performance, namely SENSGA-II. Moreover, the impacts of the network parameters are provided to draw helpful insight into the system performance. Finally, the Monte-Carlo simulation results are shown to confirm the correctness of our analysis. The results have shown that the deployment of IRS can improve the performance of this considered RF EH NOMA system by increasing the number of reflecting elements.
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Intelligent Bi-directional Relaying Communication for Edge Intelligence based Industrial IoT Networks
Appears in:
inis 22(32): 4

Authors:
Jun Liu, Yuwei Zhang, Jing Wang, Tao Cui, Lin Zhang, Chao Li, Kai Chen, Huang Huang, Xuan Zhou, Wei Zhou, Zhao Wang, Sun Li, Suili Feng, Dongqing Xie, Dahua Fan, Jianghong Ou, Jiangtao Ou, Yun Li, Haige Xiang, Kaimeno Dube, Abbarbas Muazu, Nakilavai Rono, Yajuan Tang

Published:
10th Aug 2022

Abstract:
Within this specific record, our group study the two-way interact body (TWRN) that has a number of amplify-and-forward (AF) relays. In that, the best one is actually really got to help the info communication among sources. A interact option is actually really according to the obsolete channel probl…Within this specific record, our group study the two-way interact body (TWRN) that has a number of amplify-and-forward (AF) relays. In that, the best one is actually really got to help the info communication among sources. A interact option is actually really according to the obsolete channel problem information (CSI) in addition to our group analyze its own very personal effect on the system effectiveness in the Rayleigh fading atmospheres. Especially, we extremely preliminary acquire a restricted decreased connected for the outage opportunity and afterward current an asymptotic assessment for greater signal-to-noise ratio (SNR). Our group extra acquire a restricted decreased connected along with an asymptotic result on the authorize error cost (SER). Originating got via these results, our group easily quickly obtain that body system range order remain at unity offered that the CSI is actually really obsolete. Relative results reveal the rigidness on the effectiveness bounds along with the effects of obsolete interact option on the body system effectiveness. Simulation outcomes are likewise offered to corroborate the scholastic evaluation.
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A Framework of Deploying Blockchain in Wireless Sensor Networks
Appears in:
inis 22(32): 3

Authors:
Minh Nguyen, Cuong Nguyen, Hoang T. Tran

Published:
4th Aug 2022

Abstract:
The most critical needs for wireless sensor networks (WSNs) are security, privacy, dependability, and autonomy. The networks might be vulnerable to hostile users and harmful usage if these problems are not ensured. Attacks and hazards are higher with centralized WSNs, particularly when data is shar…The most critical needs for wireless sensor networks (WSNs) are security, privacy, dependability, and autonomy. The networks might be vulnerable to hostile users and harmful usage if these problems are not ensured. Attacks and hazards are higher with centralized WSNs, particularly when data is shared with other businesses and sent between devices. In this paper, a WSN model with integrated blockchain security technology is proposed. Blockchains store the identity of each node. The validation is done by public blockchains and private blockchains. For sensor nodes, the authentication is implemented on the private blockchain. The public blockchain is used to authenticate cluster heads. Performing network attacks can easily be performed by unregistered nodes to access resources in the network. Broadcasting false information on the path of malicious nodes can increase packet latency and reduce packet delivery rate. In this paper, the model recommends the most secure nodes in the network to be used for secure routing. The main purpose is to reduce the attack of hackers from outside the network, improve the efficiency of detecting malicious nodes.
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Retina-based quality assessment of tile-coded 360-degree videos
Appears in:
inis 22(32): 2

Authors:
Viet Hung Nguyen, Ngoc Nam Pham, Cong Thang Truong, Duy Tien Bui, Huu Thanh Nguyen, Thu Huong Truong

Published:
21st Jun 2022

Abstract:
Nowadays, omnidirectional content, which delivers 360-degree views of scenes, is a significant aspect of Virtual Reality systems. While 360 video requires a lot of bandwidth, users only see visible tiles, therefore a large amount of bitrate can be saved without affecting the user’s experience on th…Nowadays, omnidirectional content, which delivers 360-degree views of scenes, is a significant aspect of Virtual Reality systems. While 360 video requires a lot of bandwidth, users only see visible tiles, therefore a large amount of bitrate can be saved without affecting the user’s experience on the service. The fact leads to current video adaptation solutions to filter out superfluous parts and extraneous bandwidth. To form a good basis for these adaptations, it is necessary to understand human’s video quality perception. In our research, we contribute to building an effective omnidirectional video database that can be applied to study the effects of the five zones of the human retina. We also design a new video quality assessment method to analyze the impacts of those zones of a 360 video according to the human retina. The proposed scheme is found to outperform 22 current objective quality measures by 11 to 31% in terms of the PCC parameter.
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Big Data and Knowledge Graph Based Fault Diagnosis for Electric Power Systems
Appears in:
inis 22(32): 1

Authors:
Yuzhong Zhou, Zhengping Lin, Liang Tu, Yufei Song, Zhengrong Wu

Published:
14th Jun 2022

Abstract:
Fault detection plays an important role in the daily maintenance of power electric system. Big data and knowledge graph (KG) have been proposed by researchers to solve many problems in industrial Internet of Things, which also give lots of potentials in improving the performance of fault detection …Fault detection plays an important role in the daily maintenance of power electric system. Big data and knowledge graph (KG) have been proposed by researchers to solve many problems in industrial Internet of Things, which also give lots of potentials in improving the performance of fault detection for electric power systems. In particular, this paper analyzes a distributed knowledge graph framework for fault detection in the electric power systems, where multiple devices train their local detection models used for fault detection assisted with a central server. Each device owns its local data set composed of historical fault information and current device state, which can be used to train a local model for fault detection. To enhance the detection performance, the distributed devices interact with each other in the KG framework, where the devices ought to achieve the regional computation in addition to the model aggregation within a specified latency threshold. Through searching for the vibrant qualities together with determined ability at the devices, we enhance the knowledge graph framework by the optimum variety of energetic devices together with the restriction of latency as well as data transmission. Particularly, two data transmission bandwidth allocation (BA) schemes are developed for the distributed knowledge graph framework, through which scheme I is actually bared after the instantaneous device state information (DSI), and scheme II utilizes particle swarm optimization (PSO) technique along with the statistical DSI. The results of simulation on the examination as well as convergence are lastly demonstrated to show the advantages of the proposed distributed KG framework in the fault detection for the electric power systems.
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Smart Grid Attacks and Countermeasures
Appears in:
inis 15(2): e4

Authors:
Eric McCary, Yang Xiao

Downloads:
2389

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:
2095

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:
1886

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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Wireless Power Transfer Near-field Technologies for Unmanned Aerial Vehicles (UAVs): A Review
Appears in:
inis 20(22): e5

Authors:
Anh M. Le, Linh H. Truong, Toan V. Quyen, Cuong V. Nguyen, Minh T. Nguyen

Downloads:
1822

Abstract:
Wireless power transfer (WPT) techniques are being popular currently with the development of midrange wireless powering and charging technology to gradually substitute the need for wired devices during charging. Unmanned Aerial Vehicles (UAVs) are also being used with many practical purposes for a…Wireless power transfer (WPT) techniques are being popular currently with the development of midrange wireless powering and charging technology to gradually substitute the need for wired devices during
charging. Unmanned Aerial Vehicles (UAVs) are also being used with many practical purposes for agriculture,
surveillance, and healthcare, etc. There is a trade-off between the weight of the UAVs or their batteries and
their flying time. In order to support those UAVs perform better in their tasks, WPT is applied in UAVs to
recharge batteries which help to increase their working time. This paper highlights up-to-date studies that are
specific to near-field WPT deploying into UAVs. The charging distances, the transfer efficiency, and transfer
power, etc. are considered to provide an overview of all common problems in using and charging UAVs,
especially for autonomous landing and charging. By classification and suggestions in specific problems will
be provided opportunities and challenges with respect to apply near-field WPT techniques for charging the
battery of UAVs and other applications in the real world.
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Improving Customer Behaviour Prediction with the Item2Item model in Recommender Systems
Appears in:
inis 18(17): e4

Authors:
T. T. S. Nguyen, P. M. T. Do, T. T. Nguyen

Downloads:
1738

Abstract:
Recommender Systems are the most well-known applications in E-commerce sites. However, the trade-off between runtime and the accuracy in making recommendations is a big challenge. This work combines several traditional techniques to reduce the limitation of each single technique and exploits the It…Recommender Systems are the most well-known applications in E-commerce sites. However, the trade-off between runtime and the accuracy in making recommendations is a big challenge. This work combines several traditional techniques to reduce the limitation of each single technique and exploits the Item2Item model to improve the prediction accuracy. As a case study, this paper focuses on user behaviour prediction in restaurant recommender systems and uses a public dataset including restaurant information and user sessions. Within this dataset, user behaviour can be discovered for the collaborative filtering, and restaurant information is extracted for the content-based filtering. The idea of the pre-trained word embedding in Natural Language Processing is utilized in the item-based collaborative filtering to find the similarity between restaurants based on user sessions. Experimental results have shown that the combination of these techniques makes valuable recommendations.
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Classification of UNSW-NB15 dataset using Exploratory Data Analysis using Ensemble Learning
Appears in:
inis 21(29): e4

Authors:
Neha Sharma, Narendra Singh Yadav, Saurabh Sharma

Downloads:
1633

Abstract:
Recent advancements in machine learning have made it a tool of choice for different classification and analytical problems. This paper deals with a critical field of computer networking: network security and the possibilities of machine learning automation in this field. We will be d…Recent advancements in machine learning have made it a tool of choice for different classification and analytical problems. This paper deals with a critical field of computer networking: network security and the possibilities of machine learning automation in this field. We will be doing exploratory data analysis on the benchmark UNSW-NB15 dataset. This dataset is a modern substitute for the outdated KDD’99 dataset as it has greater uniformity of pattern distribution. We will also implement several ensemble algorithms like Random Forest, Extra trees, AdaBoost, and XGBoost to derive insights from the data and make useful predictions. We calculated all the standard evaluation parameters for comparative analysis among all the classifiers used. This analysis gives knowledge, investigates difficulties, and future opportunities to propel machine learning in networking. This paper can give a basic understanding of data analytics in terms of security using Machine Learning techniques.
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Inpainting large missing regions based on Seam Carving
Appears in:
inis 18(16): e4

Authors:
Ahmed K. Al-Jaberi, Sabah A. Jassim, Naseer Al-Jawad

Downloads:
1595

Abstract:
Inpainting techniques are developed to recover missing image information. Existing inpainting approaches are: Partial Differential Equations Based Inpainting (PDE-BI) and Exemplar-Based Inpainting (EBI). PDE-BI methods used to fill in the missing information via information propagation from neighbo…Inpainting techniques are developed to recover missing image information. Existing inpainting approaches are: Partial Differential Equations Based Inpainting (PDE-BI) and Exemplar-Based Inpainting (EBI). PDE-BI methods used to fill in the missing information via information propagation from neighbouring areas. However, it can only reconstruct successfully small missing regions that are surrounded by limited texture. However, EBI methods are used to recover large regions with richly-textured/structured areas around them, moreover, artefacts are likely to occur. This paper proposes a technique to reduce the missing region size based on seam carving approach, which enables EBI and PDE-BI to recover the missing part. In our proposal, seam carving is used to reduce only the size of the missing region, to be subsequently recovered using EBI method. The added extra paths resulting from the added seams is repaired using PDE-BI. This method outperformed the state-of-art EBI methods.
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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:
1518

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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Security Issues in ProtoGENI
Appears in:
inis 16(6): e1

Authors:
Fnu Shalini, Yang Xiao, Bo Sun

Downloads:
1516

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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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:
1502

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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Publisher: EAI
ISSN: 2410-0218
Number of Volumes: 9

Last Published: 2022-12-20