@inproceedings{ebaddda658a848b8acc0d4dc029b8bfd,
title = "Optimizing Charging Schedules for WRSNs: A Multi-Criteria Decision-Making Approach with Multiple Charger Vehicles",
abstract = "Traditional development of wireless rechargeable sensor networks (WRSNs) focused on charger deployment, but recent research overlooked the efficient use of multiple chargers in 2-D or 3-D networks and multi-node energy transfer. This paper proposes a novel approach to address these challenges by modeling the charging scheduling problem in WRSNs with multiple Wireless Charging Vehicles (WCVs) as a multi-criteria decision-making problem. The approach involves two steps, including the enhanced k-means clustering for dividing tasks and traffic distribution and using a Fuzzy logic system to prioritize and optimize charging requests. Our extensive simulations demonstrate the effectiveness and competitiveness of our scheme, showing superior performance compared to prior approaches.",
keywords = "Charging scheduling, Fuzzy Scheduling, k-means clustering, wireless rechargeable sensor networks",
author = "Aziz, {Samah Abdel} and Ammar Hawbani and Xingfu Wang and Ismail, {A. S.} and Nasir Saeed and Alsamhi, {Saeed H.} and Liang Zhao and Ahmed Al-Dubai",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 International Conference on Microelectronics, ICM 2023 ; Conference date: 17-11-2023 Through 20-11-2023",
year = "2023",
doi = "10.1109/ICM60448.2023.10378921",
language = "English",
series = "Proceedings of the International Conference on Microelectronics, ICM",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "239--242",
booktitle = "2023 International Conference on Microelectronics, ICM 2023",
}