A Hybrid Optimization for Improving Network Performance in Scalable Mobile Ad Hoc Network

Objectives: To optimize the throughput of the network for ensure the seamless connection in a decentralized mobile ad hoc network. Methods/Statistical Analysis: This paper proposes a hybrid optimization technique (ACO-FDR PSO) of Ant Colony Optimization (ACO) integrated with Fitness Distance Ratio Particle Swarm Optimization (FDR PSO) to optimize throughput. ACO algorithm identifies unique path in the network based on higher pheromone concentration. FDR PSO optimizes throughput based on Packet Delivery Factor (PDF). Since FDR PSO employs N-best particle in the velocity update equation, the drawback of PSO such as premature convergence and getting stuck into local optimum can be prevented. Findings: Simulations performed with network simulator 2 on a 100 node network and the metrics, throughput, delay, overhead, energy and packet delivery ratio have been analyzed. Through the results it has been showed that the proposed hybrid technique achieves better results than standard AODV, ACO, PSO and ACO-PSO techniques. Application/Improvements: The proposed technique facilitates reliable transmission in emergency situations like military application, disaster management etc, where data intensive wireless networks are required.