Special Issue "10th Anniversary of Electronics: Advances in Networks"

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Networks".

Deadline for manuscript submissions: 31 October 2021.

Special Issue Editors

Prof. Dr. Dongkyun Kim
E-Mail Website
Guest Editor
Wireless & Mobile Internet Lab., School of Computer Science and Engineering, Kyungpook National University, Daegu, Korea
Interests: connected cars; vehicular ad hoc networks; the Internet of Things (machine-to-machine/device-to-device); Wi-Fi networks (including Wi-Fi Direct); wireless mesh networks; wireless sensor networks; future Internet
Special Issues and Collections in MDPI journals
Prof. Dr. Qinghe Du
E-Mail Website
Guest Editor
School of Information and Communications Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China
Interests: 5G/B5G/6G; Wireless networks; Cyber-physical systems; Blockchain; Physical-layer security, Internet-of-things
Special Issues and Collections in MDPI journals
Dr. Mehdi Sookhak
E-Mail Website
Guest Editor
School of Information Technology, Illinois State University, Illinois, USA
Interests: blockchain; cloud computing; edge computing; internet of things; vehicular networks; cryptography; AI and machine learning
Prof. Dr. Lei Shu
E-Mail Website
Guest Editor
1. College of Artificial Intelligence, Nanjing Agricultural University, Nanjing, China;
2. School of Engineering, College of Science, University of Lincoln, Lincoln LN6 7TS, UK
Interests: Internet of Things; sensor networks; green computing; cloud and fog computing; fault diagnosis; wireless sensor networks; multimedia communication; middleware; security
Special Issues and Collections in MDPI journals
Dr. Nurul I. Sarkar
E-Mail Website
Guest Editor
Network and Security Research Group, Auckland University of Technology, Auckland 1142, New Zealand
Interests: network and communications; network protocols; electronics design, vehicular ad hoc network; network design, modelling, and performance evaluation; 5G; IoT; UAV networks, wireless sensor network
Special Issues and Collections in MDPI journals
Prof. Dr. Jemal H. Abawajy
E-Mail Website
Guest Editor
Faculty of Science, Engineering and Built Environment, Deakin University, Geelong, Victoria, VIC 3220, Australia
Interests: smart healthcare system; intelligent and energy-efficient devices and applications; security of cyber physical systems for automation; fog computing; resource allocation and management; radio-frequency identification (RFID) for automating supply chain
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Electronics was founded in 2011. We are proud and excited to celebrate the 10th anniversary of the journal. On this occasion, this Special Issue is being launched to invite members of the Editorial Board, acknowledged reviewers and outstanding authors. The aim is to celebrate this important anniversary of the journal through exceptional papers fully dedicated to innovative technologies in networks and their advanced applications. Academic editors and top authors will be invited to submit high-quality papers to this Special Issue.

The subject areas of interest include, but are not limited to, the following:

  • Wireless communication and systems;
  • Computer networks;
  • Internet of Things and smart cities;
  • Pervasive computing and smart spaces;
  • Distributed system networking, cloudification and services;
  • Connected and autonomous vehicles—land, water and sky;
  • Mobile networking and computing;
  • Wireless system models and simulations;
  • Wireless system deployment and implementation;
  • Quality of service and quality of experience in wired and wireless systems;
  • Security and privacy in the aforementioned areas.

Prof. Dr. Dongkyun Kim
Prof. Dr. Qinghe Du
Dr. Mehdi Sookhak
Prof. Dr. Lei Shu
Assoc. Prof. Dr. Nurul I. Sarkar
Prof. Dr. Jemal H. Abawajy
Prof. Dr. Francisco Falcone
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (7 papers)

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Research

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Article
Determination of Traffic Characteristics of Elastic Optical Networks Nodes with Reservation Mechanisms
Electronics 2021, 10(15), 1853; https://doi.org/10.3390/electronics10151853 - 01 Aug 2021
Viewed by 301
Abstract
With the ever-increasing demand for bandwidth, appropriate mechanisms that would provide reliable and optimum service level to designated or specified traffic classes during heavy traffic loads in networks are becoming particularly sought after. One of these mechanisms is the resource reservation mechanism, in [...] Read more.
With the ever-increasing demand for bandwidth, appropriate mechanisms that would provide reliable and optimum service level to designated or specified traffic classes during heavy traffic loads in networks are becoming particularly sought after. One of these mechanisms is the resource reservation mechanism, in which parts of the resources are available only to selected (pre-defined) services. While considering modern elastic optical networks (EONs) where advanced data transmission techniques are used, an attempt was made to develop a simulation program that would make it possible to determine the traffic characteristics of the nodes in EONs. This article discusses a simulation program that has the advantage of providing the possibility to determine the loss probability for individual service classes in the nodes of an EON where the resource reservation mechanism has been introduced. The initial assumption in the article is that a Clos optical switching network is used to construct the EON nodes. The results obtained with the simulator developed by the authors will allow the influence of the introduced reservation mechanism on the loss probability of calls of individual traffic classes that are offered to the system under consideration to be determined. Full article
(This article belongs to the Special Issue 10th Anniversary of Electronics: Advances in Networks)
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Article
Multi-Layer Latency Aware Workload Assignment of E-Transport IoT Applications in Mobile Sensors Cloudlet Cloud Networks
Electronics 2021, 10(14), 1719; https://doi.org/10.3390/electronics10141719 - 17 Jul 2021
Cited by 1 | Viewed by 875
Abstract
These days, with the emerging developments in wireless communication technologies, such as 6G and 5G and the Internet of Things (IoT) sensors, the usage of E-Transport applications has been increasing progressively. These applications are E-Bus, E-Taxi, self-autonomous car, E-Train and E-Ambulance, and latency-sensitive [...] Read more.
These days, with the emerging developments in wireless communication technologies, such as 6G and 5G and the Internet of Things (IoT) sensors, the usage of E-Transport applications has been increasing progressively. These applications are E-Bus, E-Taxi, self-autonomous car, E-Train and E-Ambulance, and latency-sensitive workloads executed in the distributed cloud network. Nonetheless, many delays present in cloudlet-based cloud networks, such as communication delay, round-trip delay and migration during the workload in the cloudlet-based cloud network. However, the distributed execution of workloads at different computing nodes during the assignment is a challenging task. This paper proposes a novel Multi-layer Latency (e.g., communication delay, round-trip delay and migration delay) Aware Workload Assignment Strategy (MLAWAS) to allocate the workload of E-Transport applications into optimal computing nodes. MLAWAS consists of different components, such as the Q-Learning aware assignment and the Iterative method, which distribute workload in a dynamic environment where runtime changes of overloading and overheating remain controlled. The migration of workload and VM migration are also part of MLAWAS. The goal is to minimize the average response time of applications. Simulation results demonstrate that MLAWAS earns the minimum average response time as compared with the two other existing strategies. Full article
(This article belongs to the Special Issue 10th Anniversary of Electronics: Advances in Networks)
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Article
Deep Learning-Based Intrusion Detection for Distributed Denial of Service Attack in Agriculture 4.0
Electronics 2021, 10(11), 1257; https://doi.org/10.3390/electronics10111257 - 25 May 2021
Viewed by 906
Abstract
Smart Agriculture or Agricultural Internet of things, consists of integrating advanced technologies (e.g., NFV, SDN, 5G/6G, Blockchain, IoT, Fog, Edge, and AI) into existing farm operations to improve the quality and productivity of agricultural products. The convergence of Industry 4.0 and Intelligent Agriculture [...] Read more.
Smart Agriculture or Agricultural Internet of things, consists of integrating advanced technologies (e.g., NFV, SDN, 5G/6G, Blockchain, IoT, Fog, Edge, and AI) into existing farm operations to improve the quality and productivity of agricultural products. The convergence of Industry 4.0 and Intelligent Agriculture provides new opportunities for migration from factory agriculture to the future generation, known as Agriculture 4.0. However, since the deployment of thousands of IoT based devices is in an open field, there are many new threats in Agriculture 4.0. Security researchers are involved in this topic to ensure the safety of the system since an adversary can initiate many cyber attacks, such as DDoS attacks to making a service unavailable and then injecting false data to tell us that the agricultural equipment is safe but in reality, it has been theft. In this paper, we propose a deep learning-based intrusion detection system for DDoS attacks based on three models, namely, convolutional neural networks, deep neural networks, and recurrent neural networks. Each model’s performance is studied within two classification types (binary and multiclass) using two new real traffic datasets, namely, CIC-DDoS2019 dataset and TON_IoT dataset, which contain different types of DDoS attacks. Full article
(This article belongs to the Special Issue 10th Anniversary of Electronics: Advances in Networks)
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Article
Mitigation of the Effects of Network Outage on Video QoE Using a Sender Buffer
Electronics 2021, 10(10), 1209; https://doi.org/10.3390/electronics10101209 - 19 May 2021
Viewed by 331
Abstract
With the growth of multimedia applications and the mobile Internet, quality sense and quality expectation of the end-user are rising rapidly. A small notable distortion in the multimedia applications may degrade the degree of delight of the user, who is very considerate of [...] Read more.
With the growth of multimedia applications and the mobile Internet, quality sense and quality expectation of the end-user are rising rapidly. A small notable distortion in the multimedia applications may degrade the degree of delight of the user, who is very considerate of the video Quality of Experience (QoE). During live streaming, a network outage may result in video freezes and video jumps. To dampen the impact of a network outage on the video QoE, we propose the use of a well-sized sender buffer. We present the concept, derive key analytical relations, and perform a set of subjective tests. Based on those, we report a significant enhancement of user ratings due to the proposed sender buffer in the presence of network outages. Full article
(This article belongs to the Special Issue 10th Anniversary of Electronics: Advances in Networks)
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Article
Impact of People’s Movement on Wi-Fi Link Throughput in Indoor Propagation Environments: An Empirical Study
Electronics 2021, 10(7), 856; https://doi.org/10.3390/electronics10070856 - 03 Apr 2021
Viewed by 459
Abstract
There has been tremendous growth in the deployment of Wi-Fi 802.11-based networks in recent years. Many researchers have been investigating the performance of the Wi-Fi 802.11-based networks by exploring factors such as signal interference, radio propagation environments, and wireless protocols. However, exploring the [...] Read more.
There has been tremendous growth in the deployment of Wi-Fi 802.11-based networks in recent years. Many researchers have been investigating the performance of the Wi-Fi 802.11-based networks by exploring factors such as signal interference, radio propagation environments, and wireless protocols. However, exploring the effect of people’s movement on the Wi-Fi link throughout the performance is still a potential area yet to be explored. This paper investigates the impact of people’s movement on Wi-Fi link throughput. This is achieved by setting up experimental scenarios by using a pair of wireless laptops to file share where there is human movement between the two nodes. Wi-Fi link throughput is measured in an obstructed office block, laboratory, library, and suburban residential home environments. The collected data from the experimental study show that the performance difference between fixed and random human movement had an overall average of 2.21 ± 0.07 Mbps. Empirical results show that the impact of people’s movement (fixed and random people movements) on Wi-Fi link throughput is insignificant. The findings reported in this paper provide some insights into the effect of human movement on Wi-Fi throughputs that can help network planners for the deployment of next generation Wi-Fi systems. Full article
(This article belongs to the Special Issue 10th Anniversary of Electronics: Advances in Networks)
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Article
A Framework for Component Selection Considering Dark Sides of Artificial Intelligence: A Case Study on Autonomous Vehicle
Electronics 2021, 10(4), 384; https://doi.org/10.3390/electronics10040384 - 04 Feb 2021
Viewed by 622
Abstract
Nowadays, intelligent systems play an important role in a wide range of applications, including financial ones, smart cities, healthcare, and transportation. Most of the intelligent systems are composed of prefabricated components. Inappropriate composition of components may lead to unsafe, power-consuming, and vulnerable intelligent [...] Read more.
Nowadays, intelligent systems play an important role in a wide range of applications, including financial ones, smart cities, healthcare, and transportation. Most of the intelligent systems are composed of prefabricated components. Inappropriate composition of components may lead to unsafe, power-consuming, and vulnerable intelligent systems. Although artificial intelligence-based systems can provide various advantages for humanity, they have several dark sides that can affect our lives. Some terms, such as security, trust, privacy, safety, and fairness, relate to the dark sides of artificial intelligence, which may be inherent to the intelligent systems. Existing solutions either focus on solving a specific problem or consider the some other challenge without addressing the fundamental issues of artificial intelligence. In other words, there is no general framework to conduct a component selection process while considering the dark sides in the literature. Hence, in this paper, we proposed a new framework for the component selection of intelligent systems while considering the dark sides of artificial intelligence. This framework consists of four phases, namely, component analyzing, extracting criteria and weighting, formulating the problem as multiple knapsacks, and finding components. To the best of our knowledge, this is the first component selection framework to deal with the dark sides of artificial intelligence. We also developed a case study for the component selection issue in autonomous vehicles to demonstrate the application of the proposed framework. Six components along with four criteria (i.e., energy consumption, security, privacy, and complexity) were analyzed and weighted by experts via analytic hierarchy process (AHP) method. The results clearly show that the appropriate composition of components was selected through the proposed framework for the desired functions. Full article
(This article belongs to the Special Issue 10th Anniversary of Electronics: Advances in Networks)
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Review

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Review
Machine Learning in Wireless Sensor Networks for Smart Cities: A Survey
Electronics 2021, 10(9), 1012; https://doi.org/10.3390/electronics10091012 - 23 Apr 2021
Cited by 2 | Viewed by 1523
Abstract
Artificial intelligence (AI) and machine learning (ML) techniques have huge potential to efficiently manage the automated operation of the internet of things (IoT) nodes deployed in smart cities. In smart cities, the major IoT applications are smart traffic monitoring, smart waste management, smart [...] Read more.
Artificial intelligence (AI) and machine learning (ML) techniques have huge potential to efficiently manage the automated operation of the internet of things (IoT) nodes deployed in smart cities. In smart cities, the major IoT applications are smart traffic monitoring, smart waste management, smart buildings and patient healthcare monitoring. The small size IoT nodes based on low power Bluetooth (IEEE 802.15.1) standard and wireless sensor networks (WSN) (IEEE 802.15.4) standard are generally used for transmission of data to a remote location using gateways. The WSN based IoT (WSN-IoT) design problems include network coverage and connectivity issues, energy consumption, bandwidth requirement, network lifetime maximization, communication protocols and state of the art infrastructure. In this paper, the authors propose machine learning methods as an optimization tool for regular WSN-IoT nodes deployed in smart city applications. As per the author’s knowledge, this is the first in-depth literature survey of all ML techniques in the field of low power consumption WSN-IoT for smart cities. The results of this unique survey article show that the supervised learning algorithms have been most widely used (61%) as compared to reinforcement learning (27%) and unsupervised learning (12%) for smart city applications. Full article
(This article belongs to the Special Issue 10th Anniversary of Electronics: Advances in Networks)
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Impact of People Movement on Wi-Fi Link Throughput in Indoor Propagation Environments: An Empirical Study
Authors: Nurul I Sarkar; Osman Mussa; Sonia Gul
Affiliation: Auckland University of Technology
Abstract: none

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