Energy Optimized Routing Protocol Based on Binary Particle Swarm Optimization Successive Interference Cancellation for WSN

Abstract

A large variety of Wireless Sensor Network (WSN) applications encourage researchers to develop and improve protocols and algorithms for rising challenges. During data transmission, energy consumption is main issue because sensor nodes have limited energy capacity. In fact, WSN needs load balancing algorithms that keep use of the limited energy source to route the collected data to the receiving node. While considering adhoc network in sensitive areas, one amongst the necessary aspects to consider is energy as a result of while sending information all communicating nodes exhausts its battery life. For mobile nodes in adhoc situation one and only one source of energy is battery. As compared to single path multipath routing helps to find best path that needs less energy and enhances the network life. In this paper an energy efficient routing protocol is proposed. In routing algorithm, route that have shortest path among multipaths chosen by particle swarm optimization algorithm. Among these shortest paths, that path is chosen that need minimum route selection parameter. The proposed algorithm is based on selection of energy efficient paths from multiple shortest SIC path from source to destination. For selection Binary Particle Swarm Optimization (BPSO) algorithm is applied. The Binary Particle Swarm Optimization (BPSO) algorithm selects energy efficient route among different shortest paths. The k-shortest route is selected on the basis of bandwidth and minimum SIC. The performance of the proposed algorithm is compared with multipath Ad hoc On-Demand Distance Vector (AODV) routing protocol and concluded that BPSO optimized energy efficient path is more efficient with respect to remaining energy of the network. The result is analyzed with variable number of packets send.

Cost Optimization Approach for MANET using Particle Swarm Optimization

“…It is related to finding dynamic priority scheme which is used to select most suitable next hop by identifying them from various priority based on network condition. Result obtain by simulation shows that proposed method give better performance compare to existing geographical routing protocols by considering various parameters like PDR, end to end delay and routing overhead [9]. The Hybrid-K-means-PSO technique which is implemented to enhance the network lifetime and throughput.…”

“…For objective function search space is calculated by arranging the space of individual agents called particles. It create vector of each individual particle movement path [9]. The movement of particles are divided into two parts: i) A speculative component;…”