MSLG-RGSO: Movement score based limited grid-mobility approach using reverse Glowworm Swarm Optimization algorithm for mobile wireless sensor networks

Abstract

In mobile wireless sensor networks, two major issues are energy consumption and area coverage. To reduce the energy consumption of mobile wireless sensor networks, an efficient sensor movement is essential. But it is quite challenging to make equilibrium between energy consumption and the total area covered by the sensors. This article presents a Movement Score based Limited Grid-mobility approach using Reverse Glowworm Swarm Optimization (MSLG-RGSO) algorithm for mobile wireless sensor networks to achieve minimum energy consumption by the sensors through their optimum movements. The proposed scheme improves the efficiency of sensor networks by implementing restricted sensor movements based on movement score and effectively positioning the sensor nodes on the appropriate grid- points. Variations of the velocity of sensor nodes concerning the distance from other sensor nodes have been calculated. The simulated results exhibit that our proposed scheme reduces the energy consumption in a range of 14 - 70% in comparison with the existing Reverse Glowworm Swarm Optimization algorithm. The outcome of the simulation proves that the total distance traversed by the sensor nodes is also reduced by a range of 14 - 45% approximately in comparison with the existing approach. Hence, this proposed algorithm is accomplished as an energy-efficient approach in wireless sensor networks.