A Novel Algorithm for efficient routing in Vehicular Ad hoc Network using Swarm Intelligence optimization techniques

Abstract

Vehicular Adhoc Networks [VANETs] has emerged as one of the dynamic area of research. The main problem that raised the area of attention is routing optimization of the nodes. Though many algorithms has justified in past decade but due to dynamic movement of vehicle and various scenarios, none of the algorithm is able to fit appropriately in all the traffic scenarios. Hence, we used suggested deployment of Swarm Intelligence through Ant Colony Optimization [ACO] multi valued discrete approach that is able to find the optimize path for routing The algorithm is used by binding the features of Genetic Algorithm (GA) with ACO. This novel algorithm also provides the link stability so that frequent disconnects of the node can minimized. We demonstrated using open source simulation tools for concreteness of our algorithm. The analysis of the algorithm measured on some of the major metric of VANET routing protocols such as throughput, packet delivery ratio, normalized routing head. To verify our hypothesis we compared our simulation results with preexisting Swarm Intelligence based algorithms as in our literature.