SSOCANET -Empowering VANETs with Salp Swarm Optimization-Enhanced Clustering Algorithm
Journal Title: International Journal of Innovations in Science and Technology - Year 2024, Vol 6, Issue 2
Abstract
Vehicular Ad hoc networks (VANETs) present significant challenges due to the dynamic nature of vehicle movements, leading to a constantly changing vehicular network topology. This instability results in packet loss, network fragmentation, message reliability, and scalability issues. To address these challenges, clustering has emerged as a promising solution to escalate vehicle communication efficiency. However, determining the optimal number of clusters remains a crucial problem. The proposed solution, the Salp Swarm Optimization-Enhanced Clustering Algorithm for VANET (SSOCANET), leverages the foraging behavior of salps to optimize cluster formation based on multiple objectives. SSOCANET achieves an optimal number of clusters by employing carefully designed objective functions, minimizing communication overhead and end-to-end communication latency in a network. The simulation results demonstrate the superior performance of SSOCANET compared to other clustering approaches, offering a robust solution for VANETs.
Authors and Affiliations
Zeeshan Hidayat, Zulfiqar Ali, Shahab Haider, Iftikhar Alam, Asad Ali
Keywords
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