Genetic Algorithm with Ant Colony Optimization to Enhance Multi-Hop Routing Efficiency in Wireless Ad Hoc Network

Wireless Ad Hoc Networks (WANETs) develop multi-hop communication to transmit data packets. The unique features of WANETs make it difficult for mobile nodes to communicate reliably. Most physical routing systems do not consider stable connections during packet transmission to manage high mobility and environmental impediments, which results in increased network latency and packet loss. This paper presents a Genetic with Ant Colony Optimization (GACO) Algorithm to enhance multi-hop routing efficiency in WANET. The GACO is a hybrid model by fusing the Genetic Algorithm (GA) and Ant Colony Optimization (ACO) models. The GACO computes the fitness function to improve the accuracy for selecting the best hop. This approach uses the ACO algorithm to make a multi-hop route by applying parameters like buffer availability, loss rate, and channel load factors. In order to simulate tests of GACO performance, Network Simulator-3 is used. Comparing GACO to the baseline technique, the routing performs better.