Nature inspired route optimization in vehicular adhoc network

Recent advancements introduced in the field of wireless technologies have led to the emergence of vehicular ad hoc networks (VANETs). VANET consists of vehicles and road-side units as its components. These components communicate with each other to share the information, mainly related to traffic conditions. In such networks, routing, secure transmission of control information and user messages, avoiding traffic collisions and frequent change of topology are the main issues that arise. Therefore, offering an efficient algorithm for avoiding traffic collision is crucial to the deployment of vehicular ad hoc networks. This work deals with finding an optimized route to reach the destination while avoiding traffic collisions, using Meta heuristic optimization approach, namely Bat Algorithm. The proposed work has three modules: prediction of destination location, formation of region (by excluding invalid nodes) and finally the selection of optimized route. This work can be implemented in those application areas, where the purpose is to track the position of objects or nodes. Finally, the results are compared with standard Bat algorithm on the basis of number of iterations, number of nodes and total travelling time to reach the destination.