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This paper aims to solve the Maximum Lifetime Coverage Problem (MLCP) in Wireless Sensor Networks (WSNs) by incorporating a Learning Automaton. The proposed framework seeks to determine an optimized activity schedule that extends the network’s lifespan while ensuring that the monitoring of designated target areas meets predefined coverage requirements. The proposed algorithm harnesses the advantages of localized algorithms, including leveraging limited knowledge of neighboring nodes, fostering self-organization, and effectively prolonging the network’s longevity while maintaining the required coverage ratio in the target field.

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Learning Automata Strategies for Prolonging Lifetime of Wireless Sensor Networks

  • 会议论文

  • 发表日期：

    2025年

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  • Jakub Gąsior

摘要

This paper aims to solve the Maximum Lifetime Coverage Problem (MLCP) in Wireless Sensor Networks (WSNs) by incorporating a Learning Automaton. The proposed framework seeks to determine an optimized activity schedule that extends the network’s lifespan while ensuring that the monitoring of designated target areas meets predefined coverage requirements. The proposed algorithm harnesses the advantages of localized algorithms, including leveraging limited knowledge of neighboring nodes, fostering self-organization, and effectively prolonging the network’s longevity while maintaining the required coverage ratio in the target field.