Abstract
Replenishing energy to wireless sensor networks is always a crucial problem as the energy capacity of sensor nodes is very limited. Scheduling mobile chargers to charge sensor nodes has been widely studied due to its efficiency and flexibility. However, most existing works focus on maximizing the charging utility or charging efficiency, which ignores the task performing function of sensor nodes. In this paper, we study the mobile charger scheduling problem with the objective to maximize the task utility achieved by sensor nodes. We consider two different scenarios where sensor nodes are deployed on a line and a ring, respectively. We prove the NP-Hardness of our problems and design two approximation algorithms with guaranteed performance. We prove the approximation ratio of our algorithms through theoretical analysis, and conduct extensive simulations to validate the performance of our algorithms. Simulation results show that our algorithms always outperform the baselines, which demonstrates the effectiveness of our algorithms.
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Meng, X., Guo, J., Ding, X., Zhang, X. (2021). Optimizing Mobile Charger Scheduling for Task-Based Sensor Networks. In: Wu, W., Du, H. (eds) Algorithmic Aspects in Information and Management. AAIM 2021. Lecture Notes in Computer Science(), vol 13153. Springer, Cham. https://doi.org/10.1007/978-3-030-93176-6_12
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DOI: https://doi.org/10.1007/978-3-030-93176-6_12
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