Intelligent Resource Monitoring and Control Method in Vehicular Ad-hoc Networks for Electric Vehicle Enabled Microgrids

Raman, Dr. Arasu and Yi Ting, Nick Wong and Balakrishnan, Dr. Rajani and Sanjeevi, Dr. Baskar and Arumugam, Dr. Vijayesvaran (2024) Intelligent Resource Monitoring and Control Method in Vehicular Ad-hoc Networks for Electric Vehicle Enabled Microgrids. Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications, 15 (3). pp. 50-59. ISSN 20935374

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Abstract

Intelligent Resource Monitoring and Control Method in Vehicular Ad-hoc Networks for Electric Vehicle Enabled Microgrids Dr. Arasu Raman Nick Wong Yi Ting Dr. Rajani Balakrishnan Dr. Baskar Sanjeevi Dr. Vijayesvaran Arumugam

Software-Defined Networks (SDN) and Cloud Radio Access Networks (CRANs) are added to vehicle ad hoc networks (VANETs). The goals include making data transfer and resource sharing more efficient, achieving the shortest possible wait and response times, and ensuring the network is reliable even when conditions change. The usual ways of handling and grouping loads in Electric Vehicles (EVs), which are made for stable environments, need to be changed to work with VANETs, which are constantly evolving. To regularly meet these high service levels, focus on more adaptable and durable solutions. This study shows a software-defined EV fog computing design that improves VANETs' resource sharing. The suggested design uses smart controls placed strategically in the network to make the flow of data and use of resources as efficient as possible. The system uses parallel processing to split up computing tasks among EV stations. This makes the network more mobile and lessens the chance of jams. Simulations and real-world tests of the model show that it makes the network much more efficient. The study found that compared to traditional methods, the average response time went up by 29%, network delay went down by 23%, and it took 27% less time to get to the best assets spread.
09 30 2024 50 59 10.58346/JOWUA.2024.I3.004 https://jowua.com/wp-content/uploads/2024/10/2024.I3.004.pdf

Item Type: Article
Subjects: Electrical and Electronics Engineering > Electrical Machines
Domains: Computer Science Engineering
Depositing User: Mr IR Admin
Date Deposited: 22 Aug 2025 11:24
Last Modified: 22 Aug 2025 11:24
URI: https://ir.vistas.ac.in/id/eprint/10540

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