Improving Vehicular Ad-Hoc Network Stability Using Meta-Heuristic Algorithm

Vehicular Ad-hoc Network (VANET) is an important component of intelligent transportation systems, in which vehicles are equipped with on-board communication devices which enable vehicle-to-vehicle communication. Consequently, with regard to larger communication due to the greater number of vehicles, stability of connectivity will be a challenging problem.Clustering technique as one of the most important data mining techniques is a possible method that can improve the stability of connectivity in VANET. Therefore, this paper presentes two novel clustering algorithms based on Ant Colony System (ACS) and Artifitial Immun System (AIS) as meta-heuristic algorithms. The aim of proposed algorithms is to provide the fast clustering algorithms with high accuracy and improve the stability of VANET. A comparative study is presented to analogize the results of the proposed algorithms with six VANET clustering algorithms in the literature which are taken as benchmarks. Results reveal improvement in stability and overhead on VANET.