A Meta-Heuristic Based Approach with Modified Mutation Operation For Heterogeneous Networks

The peculiar factor of coverage called target coverage in an energy-constrained wireless sensor network is a fierce challenge nowadays. Genetic algorithm-based meta-heuristic has proven methodology while aiming to prolong the achievable network lifetime. There is a plethora of research works where maximizing the total network lifetime issue is classified as an optimization problem. In the literature, evolutionary techniques like meta-heuristics are best to use while solving an optimization problem. The task becomes more challenging due to the dense deployment of sensor nodes in the given pre-decided network. In this paper, the target coverage problem is addressed with the primary objective of maximizing the coverage of a specified set of targets with sensors with limited energy. The proposed genetic algorithm-based heuristic with modified mutation operation prolongs the network lifetime. The experimental results clearly depict that the proposed meta-heuristic performs considerably better while computing network lifetime. Besides, the performance of the proposed methodology is also compared with existing works, and it is observed that proposed algorithms perform better.