A Novel Sensor Deployment Approach Using Multi-Objective Imperialist Competitive Algorithm in Wireless Sensor Networks

A wireless sensor network is a set of spatially distributed sensor nodes that work together to cover a monitored area. Usually, a large number of sensor nodes are densely deployed because of the limited energy resources available to them. An efficient way to save energy in the system at any particular time is to activate the minimum number of sensors needed and put the remaining sensors in sleep mode. In this study, a novel multi-objective Imperialist Competitive Algorithm, called MOICA, is proposed for handling sensor deployment. The main goal is to minimize the number of active sensor nodes while achieving the maximum coverage. To illustrate the efficiency of the proposed algorithm, a set of experiments from previous studies are carried out. Numerical results indicate that with the same number of deployed sensors, MOICA can provide more accurate solutions in less computational time when compared to the existing methods, namely, coverage configuration protocol, optimal geographical density control, energy-efficient coverage control algorithm and improved geographical adaptive fidelity.