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

Vehicular ad-hoc network (VANET) is an important component of intelligent transportation systems, in which vehicles are equipped with on-board computing and communication devices which enable vehicle-to-vehicle communication. Consequently, with regard to larger communication due to the greater number of vehicles, stability of connectivity would 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. Stable communication within a VANET leads to enhanced driver safety and better traffic management. Therefore, this paper presented a novel clustering algorithm based on ant system-based algorithm called IASC in order to provide a fast clustering algorithm with high accuracy and improve the stability of VANET topology. A comparative study was proposed to analogize the results of the proposed algorithm with six VANET clustering algorithms in the literature which were taken as benchmarks. Results revealed improvement in stability and overhead on VANET.

Keywords:

Network Management , Vehicular Ad-Hoc Network (VANET) , Intelligent Transportation System (ITS) , Clustering Analysis , Ant Colony System , Meta-heuristic Algorithms