Performance improvement by optimum path routing in wireless networks

Abstract

Performance enhancement is the major requirement in wireless networks. The source and destination are fixed so parameters like throughput, average delay and network latency of the wireless network can be improved. Many algorithms are suggested by researchers to improve the performance by finding optimum path in wireless networks. Ant colony optimization (ACO) algorithms also finds optimum path with few shortcomings like when both sink and source node are closest. In this dissertation, we propose an algorithm to improve the performance of wireless network. Our proposed algorithm used clustering and ant colony optimization approach. The proposes algorithm named as Enhanced Clustering Ant Colony Routing Modified (ECACR-M). Further, the proposed algorithm has been applied on standard travelling salesman problem to obtain optimum path. We considered several quality parameters like optimum time, optimum distance and optimum path designed to analyse the result of our proposed algorithm with other algorithms reported in literature. The obtained tour length is 1-1.6% less as compared to previous reported approaches like Hybrid Particle swarm optimization while average delay is also reduced significantly. The throughput of the proposed algorithm is 9.8% increased as compared to previous reported methods like Standard ant colony routing. Proposed algorithm selects optimum route by keeping optimum time and optimum distance as major parameters and improves wireless network performance. newline newline newline newline newline newline