Mitigation of coverage and connectivity issues in wireless sensor network by multi-objective randomized grasshopper optimization based selective activation scheme

Abstract

Connectivity and coverage play a major role in the proper functioning and performance of Wireless Sensor Network (WSN). Network connectivity indicates how well the sensory data can be communicated by the sensor nodes to the sink. Coverage specifies how well a Point of Interest (POI) is being monitored by the WSN. The sensors have limited energy source, sensing, and communication range, so proper activation of the sensors have a significant influence on WSN. Therefore, the main challenge is to ensure that a small number of sensors are activated to provide coverage and connectivity in the POI. To overcome these challenges, this paper proposes a multi-objective randomized Grasshopper Optimization Algorithm-based Selective Activation (MORGOA-SA) method to sustain the expected connectivity and coverage in the network. Initially, the fitness is evaluated with five main objective functions such as (i) maximizing the coverage, (ii) Ensuring connectivity, (iii) minimizing the coverage overlap, (iv) selection of nodes with higher residual energy, and (v) minimizing active sensor nodes. Then the nodes with the best fitness function are activated, whereas the rest undergo sleep mode. Multi-objective randomized GOA-SA reduces the energy consumption of the network and prevents the failure of sensor nodes. The simulations and comparative analysis justify that the proposed MORGOA-SA scheme has attained better results than the existing schemes in terms of minimum energy consumption, minimum activation of nodes, high throughput, high connectivity, quick convergence, and increased network lifetime.