An effective hybrid genetic algorithm and tabu search for maximizing network lifetime using coverage sets scheduling in wireless sensor networks

Two important issues in Wireless Sensor Networks (WSNs) are coverage and network lifetime. Network operation in an environment can be divided into two phases, first, making coverage sets and then scheduling them. The preliminary reviews have provided a number of solutions for problem-solving in the first phase, but there is no enough solution provided for the second one. Once the number of sensors in the environment increases, the number of coverage sets as well as the number of order sequences (in which the coverage sets can be scheduled) will also increase. The present study aims to detect a near-optimal scheduling for coverage sets to prolong the network lifetime. This problem was previously introduced as MCSS (Maximum Coverage Sets Scheduling) and it was proved to be an NP-hard problem. This paper presents two algorithms, a Genetic Algorithm (GA) and a Hybrid Algorithm (HA) integrating GA and Tabu Search (TS) to solve the MCSS problem. To reveal its efficiency, the algorithms were compared with a recently proposed algorithm in terms of scheduling the coverage sets. The simulations performed in this study showed that the proposed algorithms were more successful in finding near-optimal scheduling coverage sets.