A new hybrid optimization algorithm for maximizing area coverage in wireless sensor networks

Abstract

ABSTRACT The rapid advancements in technology influence develop our lives day-by-day. However, the area coverage issue exhibited by sensor nodes in WSN still seems a complicated issue even if the area coverage enhancement models are developed. This research work is developed on the basis of implementing an efficient area coverage maximising approach with an advanced optimisation model, Coati Modernized Beluga Whale Optimisation (CMBWO). The whole process of the area coverage maximising approach revolves in two important steps: (i) Sensor node coverage model and (ii) Area coverage optimisation. In the first step, a 2D WSN monitoring area set-up is considered and in which target monitoring points are assumed to solve the coverage issue. Most importantly, the distance between the sensor node and the target monitoring point is calculated using weighted Manhattan distance evaluation instead of conventional Euclidean distance evaluation. This improvement is introduced to calculate the precise position of the target monitoring point from the position of the sensor node. The next, area coverage optimisation step is handled by the CMBWO algorithm for maximising area coverage in WSN. This hybridisation is possible by modernising BWO via COA. This efficient hybridisation led to maximising the area coverage of sensor nodes in WSN.