PSO-TLBO: A Hybrid Algorithm for Energy Optimization in Wireless Sensor Networks

Abstract

In recent times, energy optimization in wireless sensor network has become a major area of concern due to the high amount of energy expended in transmitting sensed data from the sensing node to the base station. These sensors are usually powered by a battery with limited energy to achieve its tasks which reduces the lifetime of the sensor network and hence the need for energy optimization. In this paper, a hybrid algorithm using Particle Swarm Optimization (PSO) algorithm and Teaching – Learning Based Optimization (TLBO) algorithm is proposed to selects routes from the sensing nodes to the base station. The proposed algorithm takes into consideration the residual energy and the distant of each node from the base station to determine the path of transmission of the sensed data to the end point. The performance of the PSO-TLBO algorithm was evaluated and compared with conventional PSO and TLBO algorithms based on energy consumption of the network, simulation time and statistical analysis. The results of evaluation revealed that the proposed PSO-TLBO algorithm performed better than the PSO and TLBO algorithms.