Optimization of Wireless Sensor Network using Advanced Optimization Techniques

This research study intends to optimize the wireless sensor nodes to minimize energy consumption for improving lifespan and performance of wireless networks. To align to this objective, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are used as optimization techniques in MATLAB, so that data is communicated to base stations with minimum energy consumption. Optimization needs fitness function which is based on energy consumption for sensor nodes and data transmission rates, moreover distance between the node and base station is also essential. With this ideology, it is conceptualized that sensor nodes are based on energy consumption, data transmission rates and distance from base station. PSO and GA algorithms inspect 12 sensor nodes network; position of node, energy level and data rate were different. Results obtained from both the optimization techniques are compared on basis of energy consumption and convergence rate.