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Electronics
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5G-Enabled Network Technology and Research Trend—the Future of Connectivity
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5G-Enabled Network Technology and Research Trend—the Future of Connectivity

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: closed (10 July 2022) | Viewed by 9341

Special Issue Editors

Dr. Mangal Sain

E-Mail Website
Guest Editor
Department of Information Engineering, Dongseo University, Busan 47011, Korea
Interests: Wireless Sensor network; Cloud Computing; Middleware; Ubiquitous Computing; Internet of Things
Dr. Pardeep Kumar

E-Mail Website
Guest Editor
Department of Computer Science, Swansea University, Swansea SA1 1EP, UK
Interests: Network Security; Cyber physical systems; Edge Computing; 5G/6G networks; Internet of smart things; Distributed networks; Blockchain
Prof. Dr. Madhusanka Liyanage

E-Mail Website
Guest Editor
School of computer science, University College Dublin, Belfield, Dublin 4, Ireland
Interests: 5G; blockchain; network security; virtual networks; security protocols; software-defined networking (SDN); Internet of Things (IoT); multi-access edge computing (MEC)
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues, 

Wireless sensor networks have the protentional to revolutionize many segments of our economy and life, from environmental monitoring and conservation, to manufacturing, to automation in the transportation and health care industries. The design, implementation, and operation of sensor networks require the confluence of many disciplines, including signal processing, networking and protocols, embedded systems, information management, and distributed algorithms. In the last decade, wireless networks have experienced a great amount of research and growth. Today, the internet is the beating heart of the world. Just as the roads, railways and canals provided the arteries for commerce in the Industrial Revolution, today’s network infrastructure is the circulatory system on which much of modern life depends.

As digital connectivity spreads and develops rapidly around the world, the future of the connected world is the 5G high-bandwidth and global orbiting satellite. From remote robot surgery to the introduction of autonomous vehicles and improved farming ،livestock management, 5G is set to disrupt the world's largest industrial surplus. The path of many communication providers has been stable in recent years and does not look as smooth in the next decade. Shared understanding and limited coordination enable private sector companies to build high-end and commercial platforms. The next decade will see all the new applications that can be built on this digital platform, including ones that we could not even imagine. However, while there has been substantial research in the field already, there still remain open challenges:

This Special Issue aims at publishing high-quality manuscripts covering new research on topics related to cloud computing, advances in wireless sensor networks, secure communication in wireless sensor network and cloud computing, including, but not limited to, the following:

  • 5G technologies and their use case, applications and services to fight with pandemic situation
  • Performance analysis for energy efficiency, latency and quality of experience
  • Intelligent communication technologies for B5G networks and IoE
  • P2P and blockchain-enabled secure infrastructure management for B5G networks and IoE
  • Impacts of innovative applications supported by B5G networks and IoE
  • Security and privacy for wireless sensor networks
  • IoT sensors and their applications in manufacturing services
  • Smart networking models and technologies
  • Data security, privacy and reliability for media cloud
  • Performance, availability, and scalability of Cloud services
  • Model-driven design of Cloud applications
  • UAV-assisted large-scale IoT systems, e.g., airborne sensing
  • Internet traffic offloading mechanisms using AI, blockchain, machine learning
  • Congestion control techniques in improving user experience in Internet of Things (IoT), Cloud, Edge computing networks

Technical Program Committee Members:

1. Dr. Amol Jaikar, Brookhaven National Laboratory

2. Dr. Amit Kumar Gupta, KIET Group of Institutions, Delhi NCR Ghaziabad, Uttar Pradesh

Dr. Mangal Sain
Dr. Pardeep Kumar
Dr. Madhusanka Liyanage
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 submissions that pass pre-check are 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 2400 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 (3 papers)

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Research

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13 pages, 4770 KiB  
Article
Tracking Unmanned Aerial Vehicles Based on the Kalman Filter Considering Uncertainty and Error Aware
by Mohammed Abdulhakim Al-Absi, Rui Fu, Ki-Hwan Kim, Young-Sil Lee, Ahmed Abdulhakim Al-Absi and Hoon-Jae Lee
Electronics 2021, 10(24), 3067; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10243067 - 9 Dec 2021
Cited by 1 | Viewed by 3061
Abstract
Recently, Unmanned Aerial Vehicles (UAVs) have made significant impacts on our daily lives with the advancement of technologies and their applications. Tracking UAVs have become more important because they not only provide location-based services, but are also faced with serious security threats and [...] Read more.
Recently, Unmanned Aerial Vehicles (UAVs) have made significant impacts on our daily lives with the advancement of technologies and their applications. Tracking UAVs have become more important because they not only provide location-based services, but are also faced with serious security threats and vulnerabilities. UAVs are smaller in nature, move with high speed, and operate in a low-altitude environment, which makes it conceivable to track UAVs using fixed or mobile radars. Kalman Filter (KF)-based methodologies are widely used for extracting valuable trajectory information from samples composed of noisy information. As UAVs’ trajectories resemble uncertain behavior, the traditional KF-based methodologies have poor tracking accuracy. Recently, the Diffusion-Map-based KF (DMK) was introduced for modeling uncertainties in the environment without prior knowledge. However, the model has poor accuracy when operating in environments with higher noise. In order to achieve better tracking performance, this paper presents the Uncertainty and Error-Aware KF (UEAKF) for tracking UAVs. The UEAKF-based tracking method provides a good tradeoff among preceding estimate confidence and forthcoming measurement under dynamic environments; the resulting filter is robust and nonlinear in nature. The experimental results showed that the UEAKF-based UAV tracking model achieves much better Root Mean Square Error (RMSE) performance compared to the existing particle filter-based and DMK-based UAV tracking models. Full article
(This article belongs to the Special Issue 5G-Enabled Network Technology and Research Trend—the Future of Connectivity)
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Review

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25 pages, 4015 KiB  
Review
Novel Hybrid Intelligent Secure Cloud Internet of Things Based Disease Prediction and Diagnosis
by Ankit Verma, Gaurav Agarwal, Amit Kumar Gupta and Mangal Sain
Electronics 2021, 10(23), 3013; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10233013 - 2 Dec 2021
Cited by 11 | Viewed by 2202
Abstract
Nowadays, more people are affected by various diseases such as blood pressure, heart failure, etc. The early prediction of diseases tends to increase the survival of affected patients by allowing preventive action. A key element for this purpose is the digitalization of the [...] Read more.
Nowadays, more people are affected by various diseases such as blood pressure, heart failure, etc. The early prediction of diseases tends to increase the survival of affected patients by allowing preventive action. A key element for this purpose is the digitalization of the healthcare system through the Internet of Things (IoT) and cloud computing. Nevertheless, there are major problems in the cloud with the IoT due to false predictions and errors in medical data, which results in taking a longer time to receive patient details and not providing the best outcome. Data transfer through the cloud can also be hacked by attackers due to the lack of security. This leads to a challenge for medical experts to predict the diseases accurately for a specific patient. Therefore, a novel hybrid elapid encryption (HEE) method was proposed for improving the security of cloud systems. In addition, the affected person’s disease and the severity risk level were predicted and classified using the proposed novel hybridization technique of the generalized-fuzzy-intelligence-based gray wolf ant lion optimization (GFI-GWALO) method. After the disease is predicted, the alert signal is provided to the patients. Moreover, this proposed research was implemented on MATLAB. Then the proposed simulation outcome was compared with various conventional methods and showed that the proposed method has the best outcomes in terms of its security and disease prediction with 80 ms of encryption time and 78 ms of decryption time, 100% accuracy, 99.50% precision and 8 ms of processing time. Full article
(This article belongs to the Special Issue 5G-Enabled Network Technology and Research Trend—the Future of Connectivity)
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17 pages, 4026 KiB  
Review
A Fuzzy Based Handover Decision Scheme for Mobile Devices Using Predictive Model
by Amit Kumar Gupta, Vikas Goel, Ruchi Rani Garg, Dasarada Rajagopalan Thirupurasundari, Ankit Verma and Mangal Sain
Electronics 2021, 10(16), 2016; https://0-doi-org.brum.beds.ac.uk/10.3390/electronics10162016 - 20 Aug 2021
Cited by 9 | Viewed by 2703
Abstract
Handover usually deals with the mobility of the end users in a mobile network to assure about the ongoing session of a user. It is observed that frequent handover results in call dropping due to latency. In order to overcome this issue, a [...] Read more.
Handover usually deals with the mobility of the end users in a mobile network to assure about the ongoing session of a user. It is observed that frequent handover results in call dropping due to latency. In order to overcome this issue, a fuzzy based handover decision scheme for mobile devices using a predictive model is proposed. First, an MFNN (Multi-layer Feed Forward Network) is used to determine the next cell of the user along with best hand off time. To obtain the best access network, multiple-attribute Access Network Selection Function (ANSF) is used. The fuzzy rule is applied by considering the parameter data rate, reliability, signal strength, battery power and mobility as input and the output obtained is the optimal network. The proposed scheme selects the best access network and enhances the quality of services. Full article
(This article belongs to the Special Issue 5G-Enabled Network Technology and Research Trend—the Future of Connectivity)
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