Meerkat optimizer: a novel swarm intelligent algorithm for optimizing network coverage in wireless sensor networks

Abstract Network Coverage is the significant problem of concern in Wireless Sensor Networks (WSNs) as it highly important in the rapidly evolving area of the Internet of Things (IoT). But network coverage performance optimization is highly challenging due to the complex geographical environments over which they are deployed for the objective of monitoring and achieving reactive decision making. The classical optimization algorithm faces the challenge of introducing coverage balance with respect to restricted energy resources. In this paper, Meerkat Optimizer-based Reliable Network Coverage Optimization Mechanism (MKARNCO) is proposed for improving network coverage. This adopted Meerkat Optimizer derives the merits from the hunting and alarm-raising behaviours of meerkats in nature. It specifically uses the mechanism of sentry for balancing the tradeoff between exploration and exploitation for the purpose of achieving better solution diversity and prevent local optima. The results of this MKARNCO approach in the obstacle free scenarios, conformed a coverage rate of 99.71%. It also confirmed that the proposed MKARNCO approach under the presence of obstacles confirmed a better coverage rate of 99.38%, compared to the baseline approaches.