Special Issue "Deep Learning Technologies for B5G Mobile Networks: A Themed Issue in Honor of Prof. Han-Chieh Chao"

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer and Engineering Science and Symmetry/Asymmetry".

Deadline for manuscript submissions: 31 December 2021.

Special Issue Editors

Prof. Dr. Kuo-Hui Yeh
E-Mail Website
Guest Editor
Department Information Management, National Dong Hwa University, Hualien 97401, Taiwan
Interests: IoT Security; blockchain; mobile security; NFC/RFID security; authentication; data privacy; cryptology
Special Issues and Collections in MDPI journals
Prof. Dr. Chien-Ming Chen
E-Mail Website
Guest Editor
College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, Shandong, China
Interests: network security; mobile internet; IoT; cryptography
Special Issues and Collections in MDPI journals
Dr. Wei-Che Chien
E-Mail Website
Guest Editor
Department of Computer Science and Information Engineering, National Dong Hwa University, Hualien 97401, Taiwan
Interests: Wireless Rechargeable Sensor Networks; Mobile networks; AIoT

Special Issue Information

Dear Colleagues,

Han-Chieh Chao received his MS and PhD degrees in Electrical Engineering from Purdue University, West Lafayette, Indiana, in 1989 and 1993, respectively. He is currently a professor at the Department of Electrical Engineering, National Dong Hwa University, where he also serves as president. He is also works with the Department of Computer Science and Information Engineering, National Ilan University, Taiwan. He was the Director of the Computer Center for Ministry of Education Taiwan from September 2008 to July 2010. His research interests include IPv6, cross-layer design, cloud computing, IoT, and 5G mobile networks. He has authored or co-authored four books and has published about 400 refereed professional research papers. He has supervised more than 150 MSEE thesis students and 11 PhD students. Dr. Chao has been ranked as the top 10 Computer Scientists in Taiwan for 2020 by Guide2Research. Dr. Chao was ranked as a Top 5 Taiwan Author in the field of Computer Networks & Communications, Information Systems, Computer Science Applications, and Hardware & Architecture by Scopus SciVal. Due to Dr. Chao’s contribution to suburban ICT education, he has been awarded the US President's Lifetime Achievement Award and International Albert Schweitzer Foundation Human Contribution Award in 2016.

Prof. Chao has undertaken a pioneering role in the development and promotion of practical solutions for NGN. His research accomplishments are fundamental, innovative, and insightful, which were recognized by both academia and industry. The OSI-layered protocol works well in wired networks, but the traditional layered network design cannot meet the needs of users in terms of performance and efficiency for NGN. Prof. Chao proposed "Cross-Layer Design" for 3G and 4G, which abandons the restriction that the layered architecture does not allow direct communication between adjacent layers, and can transmit or share information between different protocol layers according to system requirements, thus reducing the complexity of network planning and enhancing the flexibility of the network. The technology has also become one of the major development technologies of 5G. In this regard, he proposed novel CLD frameworks (including the integration of SDN and SDR, and STIN), and conducted systematic studies to comprehensively evaluate system performance regarding delay, traffic load, cost, and quality of service (QoS). These studies transcend the wireless access, networking, transport, and application layers, and clearly show that the proposed framework can effectively increase system capability, affordability, and sustainability.

Prof. Chao first proposed and established a novel network framework based on cross-layer design technology for the Taiwan Academic Network (TANet). He cooperated with Cisco Taiwan to build the first commercial grade 5G evolved packet core (EPC) testbed in Taiwan’s academia. This project, along with his research results, strengthened cooperation with Taiwan’s leading telecommunication company FET (Fareaastone) and Ericsson, to further develop a 5G testing on campus and set up the 5G lab in Taiwan to accelerate industrial and social transformation in the age of NGN and IoT. FET starts to offer 5G services on its LTE technology in 2018, 2 years ahead of commercial operations. In addition, the proposed STIN vision is included in the conclusion of 3GPP standard TR 38.811, as one of the working items of R16.

It is with this in mind that we honor Prof. Chao on this occasion, for his immense contributions in the areas of cross-layer design, cloud computing, IoT, and mobile networks. His excellent research results are an inspiration to all, and we are pleased to invite you to submit an article to this Special Issue of the journal Symmetry.

Symmetry is an extraordinary characteristic which has widely been deployed in different research fields of computer engineering, such as symmetric architecture for telecommunications, symmetric network structures, and symmetric algorithms. This special issue welcomes studies involving the concept of Symmetry, potential research domains include but not limited to:

• 5G/B5G/6G
• Deep learning
• Mobile networks
• Cross-layer design
• Wireless sensor networks
• Cloud computing
• Edge computing
• Internet of Things
• Software-defined networks Security and privacy

Prof. Dr. Kuo-Hui Yeh
Prof. Dr. Chien-Ming Chen
Dr. Wei-Che Chien
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. Symmetry is an international peer-reviewed open access monthly 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.

Keywords

  • 5G/B5G/6G
  • Deep learning
  • Mobile networks
  • Cross-layer design
  • Wireless sensor networks
  • Cloud computing
  • Edge computing
  • Internet of Things
  • Software-defined networks Security and privacy

Published Papers (1 paper)

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Research

Article
Genetic Algorithms with Variant Particle Swarm Optimization Based Mutation for Generic Controller Placement in Software-Defined Networks
Symmetry 2021, 13(7), 1133; https://doi.org/10.3390/sym13071133 - 24 Jun 2021
Viewed by 299
Abstract
To enable learning-based network management and optimization, the 5th Generation Mobile Communication Technology and Internet of Things systems usually involve software-defined networking (SDN) architecture and multiple SDN controllers to efficiently collect the big volume of runtime statistics, define network-wide policies, and enforce the [...] Read more.
To enable learning-based network management and optimization, the 5th Generation Mobile Communication Technology and Internet of Things systems usually involve software-defined networking (SDN) architecture and multiple SDN controllers to efficiently collect the big volume of runtime statistics, define network-wide policies, and enforce the policies over the whole network. To better plan the placement of controllers over SDN systems, this article proposes a generic controller placement problem (GCP) that considers the organization and placement of controllers as well as the switch attachment to optimize the delay between controllers and switches, the delay among controllers, and the load imbalance among controllers. To solve this problem without losing generality, a novel multi-objective genetic algorithm (MOGA) with a mutation based on a variant Particle Swarm Optimization (PSO) is proposed. This PSO chooses a global best position for a particle according to a pre-computed global best position set to lead the mutation of the particle. It successfully handles multiple conflicting objectives, fits the scenario of mutation, and can apply in many other flavors of MOGAs. Evaluations over 12 real Internet service provider networks show the effectiveness of our MOGA in reducing convergence time and improving the diversity and accuracy of the Pareto frontiers. The proposed approaches in formulating and solving the GCP in this article are general and can be applied in many other optimization problems with minor modifications. Full article
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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: Genetic Algorithms with Variant Particle Swarm Optimization Based Mutation for Generic Controller Placement in Software Defined Networks
Authors: Ling Xia Liao; Victor C. M. Leung; Zhi Li; Han-Chieh Chao
Affiliation: School of Electronic Information and Automation, Guilin University of Aerospace Technology, China
Abstract: To enable learning-based network management and optimization, 5G systems usually involve software defined networking (SDN) architecture and multiple SDN controllers to efficiently collect the big volume of runtime statistics, define network-wide policies, and enforce the policies over the whole network. To better plan the placement of controllers, this paper formulates a generic controller placement problem (GCP) that considers the organization of controllers and optimizes both controller placements and switch assignments to minimize the controller-to-switch delay, controller-to-controller delay, and controller load imbalance. To solve this problem without losing generality, we propose a novel multi-objective genetic algorithm (MOGA) utilizing a variant Particle Swarm Optimization (PSO) based mutation. This PSO chooses a global best position for a particle according to a pre-calculated global best position set to guide the mutation of the particle. It successfully handles multiple conflicting objectives, fits the scenario of mutation, and can apply in many other flavors of MOGAs. Evaluations over 12 real Internet service provider networks show the effectiveness of our MOGA in reducing convergence time and improving diversity and accuracy of the pareto frontiers. Approaches in formulating and solving the GCP are general, and can be applied in many other optimization problems with minor modifications.

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