Fuzzy Logic with Hybrid Optimization Approach for Optimal Route Selection in MANET

Abstract

Independent, self-governing, mobile wireless hosts communicating through wireless links and forming a temporary network dynamically without centralized infrastructure are called Mobile Ad-hoc Networks (MANETs). As MANET nodes are not stationary, the same routing path may not always be taken between sender and receiver(s). Hence, such routing is complicated. Literature proposes different routing protocols each having advantages and limitations. This study proposes fuzzy logic with hybrid optimization approach for optimal route selection in MANET applications. The proposed hybrid optimization is based on Genetic Algorithm (GA) and Hill Climbing algorithm. Fuzzy rule system is based on actual end to end delay, when a node leaves the network, number of packets dropped and number of RRER generated. Simulation results demonstrate the efficiency of the proposed hybrid fuzzy routing when compared to Ad hoc On-demand Distance Vector routing (AODV)