Parameter Value Optimization of Ad-hoc on Demand Multipath Distance Vector Routing Using Particle Swarm Optimization

The performance of routing protocol in Vehicular ad-hoc network (VANET) depends on value of parameters used in. Being very large combination of these values, it is difficult to find an optimal combination for better QoS in VANET. Therefore, we have proposed an algorithm based on Particle Swarm Optimization (PSO) to find an optimal combination in Ad-hoc on demand multipath distance vector routing (AOMDV) in real scenario. The experimental results show 80.65% drop in Average End-to-End delay (AE2ED), 37.07% drop in Network Routing Load (NRL) and slight drop (1.96%) in Packet Delivery Ratio (PDR) using optimal combination of value of parameters.