Special Issue Information Special Issue Call for Paper Other Special Issues on this journal Closed Special Issues
Deep Reinforcement Learning for Future Wireless Network Virtualization

Deep Reinforcement Learning for Future Wireless Network Virtualization

Journal
Impact Score 5.45

OFFICIAL WEBSITE

Special Issue Information

Submission Deadline: 15-06-2021
Journal Impact Score: 5.45
Journal Name: Computer Communications
Publisher: Computer Communications

Special Issue Call for Papers


Providing wireless network virtualization is a promising idea that has the potential to alleviate spectrum congestion and open up new network services. The paradigms differ with the degree of virtualization and sharing of resources. Each paradigm involves technological and non-technical challenges that must be resolved before a widespread technology becomes wireless virtualization. These problems require careful design and assessment for the virtualization of wireless networks to be a success. The design of future wireless networks needs to satisfy numerous criteria for Quality of Service (QoS). From wired to wireless networks, virtualization has been expanded. It enhances efficiency and utilisation and allows multi-tenancy and customised service with broader range of carrier frequencies. Due to the dynamic and unpredictable network status and heterogeneity of wireless users in IoT environment, network control problems are very challenging as the dimensionality and computational complexity rapidly increase. Also in the wireless domains such as WiFi, cellular network and wireless Internet of Things (IoT), new architectures involving virtualization have been evolving. In infrastructure-based wireless networks, relatively little virtualization has occurred, but the concept of virtualizing wireless access is gaining attention as it has the potential to enhance the use of spectrum and perhaps create new services. Virtualization of the wireless network requires both sharing of resources and spectrum sharing. Therefore, rational planning and resource allocation to provide entire network architecture, the QoS promised by each SP, mobility management and the spatial-temporal variations of traffic, cross INP signaling and location tracking contributes to vital research areas in Wireless Network Virtualization.



Deep Reinforcement Learning (DRL) has been developed by the use of Deep Neural Networks (DNNs) as a potential approach to solve high-dimensional and continuous control issues effectively. Deep Reinforcement Learning techniques provide great potential in IoT, edge and SDN scenarios and are used in heterogeneous networks for IoT-based energy management based on the QoS required by each Software Defined Network (SDN) service. Current research focuses on the implementation and validation of the Software-Defined Networks and Network Function Virtualization in Global Edge Computing Architecture, developing intelligent mechanisms that allow automated and dynamic management of the virtual communications established in the SDNs by user nodes. While DRL has shown great potential to solve emerging problems in complex wireless network virtualization, there are still domain-specific challenges that require further study, including the design of adequate DNN architectures with 5G network optimization issues, resource discovery and allocation, developing intelligent mechanisms that allow the automated and dynamic management of the virtual communications established in the SDNs which is considered as research perspective



The objective of this specific issue is to explore recent developments in DRL and address practical challenges in Wireless Network Virtualization that promote researchers to present their research on the innovative DRL system, network modelling and architecture, technical challenges in terms of instantiation, operation and management of wireless network virtualization.



Original research and review articles in this area are encouraged in the following topic areas including, but are not limited to:




Tentative SI Timeline:



Manuscript Submission Deadline Date: 15, June 2021



Authors Notification Date: 20, August 2021



Revised Papers Due Date: 25, November 2021



Final notification Date: 05, February 2022



Guest Editor Details:



Lead Guest Editor:



Dr. Tu Nguyen
Assistant Professor,
Department of Computer Science,
Purdue University Fort Wayne,
Fort Wayne, USA.
Email: [email protected]
URL: https://users.pfw.edu/nguyent/



Dr. TU NGUYEN is currently an Assistant Professor in the Department of Computer Science, Purdue University Fort Wayne. He earned the Ph.D. degree in electronic engineering from the National Kaohsiung University of Science and Technology (formerly, National Kaohsiung University of Applied Sciences) in 2016. He was a Postdoctoral Associate in the Department of Computer Science & Engineering, University of Minnesota - Twin Cities in 2017. Prior to joining the University of Minnesota, he joined the Missouri University of Science and Technology as a Postdoctoral Researcher in the Intelligent Systems Center in 2016. His research interests include design and analysis of algorithms, network science, cyber-physical systems, and cybersecurity. He currently serves as an Associate Editor for IEEE Access (2019- ) and EURASIP Journal on Wireless Communications and Networking (2017- ). He is also on the Editorial Board of the Cybersecurity journal, Internet Technology Letters (2017- ), International Journal of Vehicle Information and Communication Systems (2017- ), International Journal of Intelligent Systems Design and Computing (2017- ), and IET Wireless Sensor Systems (2017- ), and has served as a TPC Chair for the NICS 2019, SoftCOM (25th), and ICCASA 2017, a Publicity Chair for iCAST 2017 and Big Data Security 2017, and a Track Chair for ACT 2017. He has also served as a technical program committee member for over 100 premium conferences in the areas of network and communication such as INFOCOM, Globecom, ICC, and RFID. He is a senior member of the IEEE.



First Co- Guest Editor:



Dr. Nam P. Nguyen
Associate Professor,
Department of Information and Computer Sciences,
Towson University,
USA.
Email: [email protected]
Google Scholar: https://scholar.google.com/citations?user=aJcBWkgAAAAJ&hl=en



Dr. Nam Nguyen is currently an Associate Professor in the Information and Computer Sciences Department, Towson University, USA. Dr. Nguyen received his PhD in Computer Engineering from the University of Florida, USA. His research interests include Social network analysis & Big Data mining, Cyber Security and Mobile-aware computing. Dr. Nguyen currently serves in the Editorial board of the Computational Social Networks journal, the Mathematical Foundations of Computing journal, and Frontiers in Big Data journal. Dr. Nguyen has been serving as organization and TPC member for several conferences including IEEE Infocom, ACM Hypertext, IJCAI, etc. Dr. Nguyen has also been a panelist serving several National Science Foundation panels.



Second Co- Guest Editor:



Dr.Claudio Savaglio
Department of Computer Science, Modeling,
Electronics and Systems Engineering (DIMES),
University of Calabria, Italy.
Email: [email protected]
Google Scholar: https://scholar.google.it/citations?user=VR5qJdIAAAAJ&hl=en



Dr. CLAUDIO SAVAGLIO is a Researcher at ICAR-CNR Institute, Italy. He received the Ph.D. degree in ICT from the University of Calabria (Unical), Italy, in 2018. Dr. Savaglio was a Visiting Researcher at the University of Texas at Dallas (TX, USA) in 2013, at the New Jersey Institute of Technology (NJ, USA) in 2016, and at the Universitat Politècnica de València (Spain) in 2017. He was also Temporary Research Fellow at the University of Calabria (Unical), where he was Teacher Assistant and Adjunct Professor (2018-2020). He currently serves as Guest Editor for the Journal of Computers & Electrical Engineering (CAEE), Sensors and IET journal. He has also served as a technical program committee member for many premium conferences in the areas of IoT, computer communications and networks such as GIOTS, ICC, and ICCCN. He has published more than 40 prestigious conference and journal papers. His research interests include the Internet of Things (IoT), network simulation, edge computing, and agent-oriented development methodologies.



Third Co- Guest Editor:



Dr. Ying Zhang
School of Information and Communication Engineering,
University of Electronic Science and Technology of China
Email: [email protected]
Google Scholar: https://scholar.google.com/citations?hl=de&user=MwnsRL8AAAAJ&view_op=list_works&sortby=pubdate



Dr. YIN ZHANG is a Full Professor of the School of Information and Communication Engineering, University of Electronic Science and Technology of China. He is a Distinguished Scholar of Hubei Province, China. He is Co-chair of IEEE Computer Society Big Data STC. He serves as editor or associate editor for IEEE Network, Information Fusion, IEEE Access, etc. He is a Guest Editor for IEEE Transactions on Network Science and Engineering, Future Generation Computer Systems, IEEE IoT Journal, ACM/Springer Mobile Networks & Applications, Sensors, Neural Computing and Applications, Multimedia Tools and Applications, Wireless Communications and Mobile Computing, Electronic Markets, Journal of Medical Systems, New Review of Hypermedia and Multimedia, etc. He also served as Track Chair of IEEE CSCN 2017, TPC Co-Chair of CloudComp 2015 and TRIDENTCOM 2017, etc. He has published more than 100 prestigious conference and journal papers, including 14 ESI Highly Cited Papers. He is an IEEE Senior Member since 2016. He got the Systems Journal Best Paper Award of the IEEE Systems Council in 2018. He was named in Clarivate Analytics Highly Cited Researchers List in 2019. His research interests include mobile computing, edge intelligence, cognitive wireless communications, etc

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G2R Score
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