부산대학교 도서관

In city environments, routing remains a more challenging process for Vehicular Adhoc Networks(VANETs). In recent years, identifying an optimal end-to-end path that reduces overhead and delays has been challenging and limited. It is due to the increased movement of vehicles, the repeated failures of a path and the variety of obstacles that may impact the consistency of data routing and transmission that these limitations exist. Thus, this paper presents an enhanced VANET routing model that incorporates congestion, travel, collision and QoS awareness costs. Accordingly, in the proposed work, a cost model is modeled as the solution for the vehicle routing problem by taking into account the above-mentioned constraints. In addition, the Fuzzification of the QoS factor is considered along with the total routing cost. The work gets proceeded by intending to find the optimal route that concerns the minimized routing cost. For determining the optimal route, this research work establishes a new hybrid algorithm known as Grey Updated Butterfly Operator (GU-BO) that links both the concepts of Monarch Butterfly Optimization (MBO) Algorithm and Grey Wolf Optimization (GWO). Finally, the performance of the implemented approach is compared over other conventional approaches namely, Particle Swarm Optimization (PSO), Firefly algorithm (FF), Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WAO), Jaya Algorithm (JA), MBO, and Mean Computing Jaya Algorithm (MC-JA) with respect to convergence analysis and cost analysis, and proves its superiority of proposed work over others.