Article: Distributed clustering and operational state scheduling in wireless rechargeable sensor networks Journal: International Journal of Sensor Networks (IJSNET) 2020 Vol.34 No.1 pp.26 - 37 Abstract: Replacement of exhausted batteries in wireless sensor networks might lead to temporal disruption of network operations. Wireless rechargeable sensor networks (WRSNs) can mitigate this problem by recharging nodes before they run out of batteries. However, because WSRN nodes cannot perform recharging and task monitoring simultaneously, it is challenging to ensure continuous network operations while maintaining low-cost and low processing-power requirements of nodes. It is necessary to design an effective and energy-efficient node scheduling scheme to schedule nodes to either monitoring or recharging state without adversely reducing the network lifetime and throughput. In this paper, we propose a distributed clustering and operational state scheduling algorithm (DCOS) to maximise the overall network lifetime. Nodes needing energy can be replenished within time intervals when they are not in the state of sensing and transmitting. We conducted extensive simulations to evaluate the performance of DCOS. The results show that DCOS outperforms most of the state-of-the-art methods. Inderscience Publishers - linking academia, business and industry through research

Title: Distributed clustering and operational state scheduling in wireless rechargeable sensor networks

Authors: Shamsuddeen Abdullahi Mikail; Jianxin Wang; Shigeng Zhang

Addresses: School of Computer Science and Engineering, Central South University, Hunan, Changsha, 410-083, China ' School of Computer Science and Engineering, Central South University, Hunan, Changsha, 410-083, China ' School of Computer Science and Engineering, Central South University, Hunan, Changsha, 410-083, China

Abstract: Replacement of exhausted batteries in wireless sensor networks might lead to temporal disruption of network operations. Wireless rechargeable sensor networks (WRSNs) can mitigate this problem by recharging nodes before they run out of batteries. However, because WSRN nodes cannot perform recharging and task monitoring simultaneously, it is challenging to ensure continuous network operations while maintaining low-cost and low processing-power requirements of nodes. It is necessary to design an effective and energy-efficient node scheduling scheme to schedule nodes to either monitoring or recharging state without adversely reducing the network lifetime and throughput. In this paper, we propose a distributed clustering and operational state scheduling algorithm (DCOS) to maximise the overall network lifetime. Nodes needing energy can be replenished within time intervals when they are not in the state of sensing and transmitting. We conducted extensive simulations to evaluate the performance of DCOS. The results show that DCOS outperforms most of the state-of-the-art methods.

Keywords: WRSNs; wireless rechargeable sensor networks; wireless charging; clustering; algorithm; operational state scheduling; mobile charger; wireless recharger; partial recharging; periodic recharging; static nodes.

DOI: 10.1504/IJSNET.2020.109716

International Journal of Sensor Networks, 2020 Vol.34 No.1, pp.26 - 37

Received: 13 Dec 2019
Accepted: 11 Feb 2020
Published online: 21 Sep 2020 *

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Title: Distributed clustering and operational state scheduling in wireless rechargeable sensor networks

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