LBSMT: Load Balancing Switch Migration Algorithm for Cooperative Communication Intelligent Transportation Systems

Babbar, Himanshi, Rani, Shalli, Bashir, Ali Kashif and Nawaz, Raheel ORCID: https://orcid.org/0000-0001-9588-0052 (2022) LBSMT: Load Balancing Switch Migration Algorithm for Cooperative Communication Intelligent Transportation Systems. IEEE Transactions on Green Communications and Networking, 6 (3). pp. 1386-1395. ISSN 2473-2400

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Official URL: https://ieeexplore.ieee.org/document/9743414

Abstract

We entered an era when the automotive industry is undergoing a digital revolution. Automobiles evolving into automated movable objects are using artificial intelligence capabilities. In contrast, cellular communications networks incorporate emerging technologies, such as SDN (software-defined networking) and NFV (network functions virtualization). Sophisticated software-defined communications networks virtualizes network functions and paving the way for the new design, monitoring, and management strategies. SDN is rising towards the application of load balancing for real time applications due to the heavy load of data on servers. When there is intra-communication between the various switches and domains; migration of switches takes place and the load over servers is imbalanced. An imbalance of the load will increase the response time and decrease the throughput. In intelligent transportation systems (ITS) balance on the servers should be maintained for the network sustainability. To provide a solution for the requirement of ITS, a dynamic QoS-aware load balancing switch migration algorithm (LBSMT) is proposed in this paper. As per the results validated in Python, after the migration LBSWT has improved CPU utilization, memory utilization, throughput and response time over server load, round robin, weighted round robin, LBBSRT and dynamic server algorithms.

Item Type:	Article
Peer-reviewed:	Yes
Date Deposited:	30 Mar 2022 20:08
Publisher:	Institute of Electrical and Electronics Engineers
Additional Information:	This is an Author Accepted Manuscript of an article published in IEEE Transactions on Green Communications and Networking by Institute of Electrical and Electronics Engineers. © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Divisions:	Faculties > Business and Law Faculties > Science and Engineering Research Centres > Centre for Advanced Computational Science
URI:	https://mmu-uat.leaf.cosector.com/id/eprint/629426
DOI:	https://doi.org/10.1109/tgcn.2022.3162237
ISSN	2473-2400
e-ISSN	2473-2400

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