An improved whale optimization algorithm solving the point coverage problem in wireless sensor networks

In wireless sensor networks (WSNs), coverage and quality detection are the aspects which are extremely significant in criteria such as quality of service and power consumption reduction. Network lifespan in wireless sensor network (WSN) applications is a critical section for the network coverage due to the power limitation and incapability of battery replacement. Providing a smart and powerful tool for solving point coverage problem has always attracted many researchers. Meta-heuristic algorithms, usually inspired by nature and physical processes, are currently being used as one of the most powerful methods to solve such complex optimization problems. Therefore, this paper proposes an improved meta-heuristic algorithm based on whale optimization algorithm (WOA) to solve the network coverage problem. The proposed algorithm tries to find the best solution (BS) based on three proposed operations of exploration, spiral attack, and bubble-net attack of whales. Since the WOA has been proposed for continuous problems and has not been used for discrete problems so far, a discretization technique of this algorithm for the point coverage problem in WSN is also presented in this paper. Several scenarios, including medium, hard and complex problems, are designed to evaluate the proposed technique, and it is compared to genetic algorithm (GA) and ant colony optimization (ACO) based on time complexity criteria in providing a suitable coverage and network lifetime. The experimental results show that the proposed algorithm outperforms the compared algorithms in most scenarios with increasing the lifespan of the coverage area.