Imperialist competitive algorithm for energy-efficient clustering in wireless sensor network

Abstract

This project proposes an energy-efficient cluster head selection algorithm for the clustering of heterogeneous Wireless Sensor Network (WSN) inspired by imperialistic competition called Imperialist Competitive Algorithm (ICA). The main contribution of the work is the employment of the metaheuristic algorithm to solve NP-hard (non-deterministic polynomial) problem for the sake of reducing network energy consumption and subsequently extends the sensor network lifetime. This is achieved by first transforming the clustering problem into an optimization problem and then several cost functions are taken into consideration for the selection of optimal set of cluster heads such that the transmission distance between cluster heads to their respective cluster members as well as total network energy consumption in the network are minimized. In correspond for evaluating the effectiveness of the proposed algorithm, MATLAB simulations are carried out in different network scenarios. The performance of the ICA is evaluated against other widely-use evolutionary algorithm to demonstrate that the cluster-based protocol using ICA can significantly achieve improvement in terms of network lifetime, total data delivery and energy consumption of the network. The work can be considered significant due to the fact that the algorithm proposed in this project is therefore dynamic because it is able to adapt to the changes in various sensor network architectures and network growth. Besides that, the simulation results shown that the proposed algorithm can improve the lifetime of WSN up to 36 % compared to its comparative (which is LEACH-C protocol).