Abstract:

Vehicular Ad-Hoc Networks (VANETs) is extremely developing nowadays in various applications of Intelligent Transport Systems (ITS). VANETs are highly mobile in nature, vehicles are travelling in high speed so due to this communication becomes ineffective in VANETs that results in the increase of delay and packet loss during data transmission. So it is essential to develop a model to obtain intelligent path selection in VANETs. In this paper, Hybrid Particle based Artificial Fish Swarm Optimization (HP-AFSO) approach is introduced to enhance the path selection process during the process communication in VANETs. The proposed HP-AFSO approach is the combination of particle swarm optimization (PSO) algorithm and Artificial Fish Swarm Optimization (AFSO) algorithm. In this network, vehicles are separated into two types which are ordinary vehicles and high-speed vehicles (smart vehicles). Here PSO algorithm is used to provide optimal path to the ordinary vehicles and AFSO algorithm provide optimal path to the smart vehicles where these vehicles acquire highest priority in path selection and transmission. As the result the high-speed vehicles are separated and those will not affect the network by increasing the congestion. The simulation is carried out in NS2.35 and four parameters are used for the analysis of performance evaluation such as packet delivery ratio, end to end delay, packet loss.