International Journal of Computer Networks and Applications (IJCNA)

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International Journal of Computer Networks and Applications (IJCNA)

International Journal of Computer Networks and Applications (IJCNA)

Published By EverScience Publications

ISSN : 2395-0455

Dynamic Integration of Fast Furious Cheetah Optimization for Efficient and Secure Routing in Vehicular Ad Hoc Networks

Author NameAuthor Details

A. Sheela Rini, C. Meena

A. Sheela Rini[1]

C. Meena[2]

[1]Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India.

[2]Department of Computer Science, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu, India.

Cite this Article

DOI: 10.22247/ijcna/2024/224449

Pages : 248-273

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Abstract

This research delves into the intricate challenges of routing efficiency and data security in Vehicular Ad Hoc Networks (VANETs), characterized by the dynamic nature of Vehicle-to-Vehicle (V2V) communication. To address the former, this research proposes Route Life Time Enhanced AODV (RLE-AODV), a mechanism designed to prolong route stability by optimizing the Ad Hoc On-Demand Distance Vector (AODV) protocol. Concurrently, recognizing the paramount importance of securing transmitted data in V2V communication, Elliptic Curve Cryptography (ECC) is an encryption technique to fortify the integrity and confidentiality of exchanged information. The study then introduces Fast Furious Cheetah Optimization (FFCO) as an innovative approach aimed at a unified optimization of RLE-AODV and ECC. FFCO is a metaheuristic optimization algorithm orchestrating a harmonious integration of routing efficiency and security enhancement. The intricacies of this integration are technically expounded, elucidating how FFCO optimally adjusts parameters within RLE-AODV and ECC to achieve a synergistic and mutually reinforcing effect. Simulations are conducted meticulously to evaluate the proposed framework's technical prowess. The results underscore the superior performance and heightened security of integrating FFCO with RLE-AODV and ECC in V2V VANETs. This research contributes to advancing efficient and secure vehicular communication and offers valuable insights into the synergy of optimization techniques for multifaceted network challenges.

Index Terms

Ad Hoc On-Demand Distance Vector Routing

Particle Swarm Optimization

Machine Learning

Network Lifespan

Energy Balancing

Localization

Clustering

Routing Overhead

Throughput

End-to-End Delay

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