INTELLIGENT DEPLOYMENT STRATEGY FOR HETEROGENEOUS NODES TO INCREASE THE NETWORK LIFETIME OF WIRELESS SENSOR NETWORKS

Abstract

The deployment plan of the sensors is among the most important design features of Wireless Sensor Networks. Generally, there are two types of WSN deployment strategies : random and planned deployment. I center on planned deployment in this report, which is specified as selecting sensor sites to achieve multiple WSN design objectives under certain constraints. In this research, Particle Swarm Optimization and Genetic Algorithm are the two different mathematical methodologies discussed. I have examined basics and fundamental mathematical foundations for each strategy. The algorithms associated with each technique are then studied, and a comparison of their goals and performance is made. Here, I also propose intelligent deployment strategies for heterogeneous node deployment in wireless sensor networks. Placing the nodes in a wireless sensor network is a difficult problem, so I use Particle Swarm Optimization (PSO) algorithm and Genetic Algorithm (GA) to find the optimal location of the heterogeneous nodes thereby increasing the network lifetime. The routing protocols used in this implementation are direct routing protocol and multi-hop routing protocol. After performing many experiments, I found that the proposed methods increase the network lifetime on average up to 150% of the initial lifetime. The objective function used by the models is the inverse of a lifetime and I tracked lifetime and time taken to reach a solution for comparing GA and PSO.