Impact of hybridized rider optimization with cuckoo search algorithm on optimal VANET routing

Abstract

SummaryVANET routing is a serious concern due to some of the limitations in terms of routing costs. More research has already worked on VANET routing strategies for enhancing the performance of the network. However, optimal route selection is a tedious or complex issue in this scenario. To cope with this issue, this research work attempts to introduce a new VANET routing model that considers certain network quality measures such as congestion, travel, collision, and QoS awareness cost. A new cost model is designed based on the given constraints. Along with this, the fuzzification of the QoS factor is considered along with the total routing cost. This work determines the optimal route selection with minimized routing cost by employing a novel optimization algorithm called Rider Integrated Cuckoo Search (RI‐CS) that hybridizes the concept of Rider Optimization Algorithm (ROA) and Cuckoo Search (CS). Finally, the performance of the proposed RI‐CS is analyzed against the conventional models like Particle Swarm Optimization (PSO), Firefly algorithm (FA), Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WAO), ROA, CS, Mean Computing Jaya Algorithm (MC‐JA), and Grey Updated Butterfly Operator (GU‐BO) in terms of certain cost analysis.