Evaluating The Efficiency Of Genetic Algorithm-Based Routing In MANET’s

Abstract

Due to the inherent instability of mobile ad hoc networks (MANETs), frequent node mobility, bandwidth constraint, and energy constraint are some of the problems that render effective routing an uphill task. Although the standard routing systems such as the AOMDV provide reliable path solutions, they do not necessarily provide the best solutions to optimizing the performance of networks in circumstances where the environment is becoming volatile. This paper uses the Network Simulator 2 (NS2) simulation to compare the performance of an AOMDV-based routing strategy with that of a Genetic Algorithms (GA)-based routing strategy. The simulation parameters are a node range of 40-120, a size of 1250 x 1250 m, the IEEE 802.11 MAC protocol and a transmission range of 250 m. Performance is measured by three major measures, which include end-to-end latency, packet delivery ratio, and throughput. The GA-based protocol based on the outcomes of the experiments minimizes the delay in high mobility situations and attains better rates of packet delivery and throughput. To enhance the efficiency and stability of MANET, the findings suggest that improvement of adaptability and robustness of routing solutions can be provided by evolutionary computation methods.