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SDN-Based Edge Computing in Vehicular Communication Networks: A Survey of Existing Approaches

Ul Haq, Syed Aizaz, Imran, Muqaddas, Shah, Nadir and Muntean, Gabriel-Miro orcid logoORCID: 0000-0002-9332-4770 (2025) SDN-Based Edge Computing in Vehicular Communication Networks: A Survey of Existing Approaches. IEEE Access, 13 . ISSN 2169-3536

Abstract
Improved communication performance in vehicular communication networks (VCN) is achieved by enabling additional computation and storage support at the levels of edge, fog, and cloud. Specifically, the edge/fog servers located near vehicles enable improved networking performance, especially in terms of load balancing and end-to-end delay. Recently, Software Defined Networking (SDN) in general and SDN-based edge/fog computing in particular have been employed in the context of VCN, enabling further communications performance improvements to be achieved with the help of SDN-based fog/edge computing in the VCN (SDV-F). This paper surveys a large number of innovative approaches proposed for communications performance enhancement in the context of SDV-F and categorizes them based on different aspects, including Artificial Intelligence (AI) and security support. The advantages and limitations of the proposed approaches in each category are highlighted. Finally, various directions that can be considered as promising research avenues by researchers in the future are presented and discussed.
Metadata
Item Type:Article (Published)
Refereed:Yes
Uncontrolled Keywords:SDN, edge computing, vehicular network, AI.
Subjects:Engineering > Electronic engineering
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Publisher:Institute of Electrical and Electronics Engineers
Official URL:http://ieeexplore.ieee.org.dcu.idm.oclc.org/xpl/mo...
Copyright Information:Authors
ID Code:31037
Deposited On:06 May 2025 11:20 by Gordon Kennedy . Last Modified 06 May 2025 11:20
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