Abstract
Wireless sensor networks (WSNs) are a rapidly developing field of study with many uses. Sensor nodes typically have restricted energy in utility applications. To successfully increase the network lifetime, energy consumption must be managed. This paper aims at programming sensor availability and activity to enhance network coverage lifetime. The typical strategy is to consider subsets of nodes that cover each target continually. These subsets often referred to as cover sets, are then shifted to active mode while the rest are in low-power or sleep mode. This problem is NP-hard and is known as the Maximum Coverage Set Scheduling Problem (MCSS). In this research, the genetic algorithm is adapted to prolong WSN lifetime. The proposed method was compared with Greedy-MCSS and MCSSA algorithms. The simulation results demonstrate the importance and beneficial effects of using genetic algorithm in our solution.
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Larhlimi, I., Lachgar, M., Ouchitachen, H., Darif, A., Mouncif, H. (2023). Contribution to Solving the Cover Set Scheduling Problem and Maximizing Wireless Sensor Networks Lifetime Using an Adapted Genetic Algorithm. In: Masrour, T., Ramchoun, H., Hajji, T., Hosni, M. (eds) Artificial Intelligence and Industrial Applications. A2IA 2023. Lecture Notes in Networks and Systems, vol 772. Springer, Cham. https://doi.org/10.1007/978-3-031-43520-1_11
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