Research Article
A Sleep Scheduling Algorithm with Limited Energy Collection in Energy Harvesting Wireless Sensor Networks
@INPROCEEDINGS{10.1007/978-3-030-94763-7_21, author={Fei Gao and Wuyungerile Li and Pengyu Li and Ruihong Wang}, title={A Sleep Scheduling Algorithm with Limited Energy Collection in Energy Harvesting Wireless Sensor Networks}, proceedings={Mobile Networks and Management. 11th EAI International Conference, MONAMI 2021, Virtual Event, October 27-29, 2021, Proceedings}, proceedings_a={MONAMI}, year={2022}, month={1}, keywords={WSN EH-WSN Sleep scheduling Network lifetime}, doi={10.1007/978-3-030-94763-7_21} }- Fei Gao
Wuyungerile Li
Pengyu Li
Ruihong Wang
Year: 2022
A Sleep Scheduling Algorithm with Limited Energy Collection in Energy Harvesting Wireless Sensor Networks
MONAMI
Springer
DOI: 10.1007/978-3-030-94763-7_21
Abstract
Energy harvesting wireless sensor networks (EH-WSNs) have been widely studied. However, in the case of limited illumination time or weak illumination intensity in winter or cloudy days, energy harvested by nodes is also limited, which leads to the corresponding reduction of network lifetime. Therefore, this paper proposes a Sleep scheduling algorithm based on virtual Grid for Limited Energy collection energy harvesting (SGLE), which consists of two parts: (1) A judgment criteria of redundant nodes; The network monitoring region is divided into several small squares of equal area, The network monitoring region is divided into several equal areas, and the covering ratio of the node’s sensing region by its neighbor nodes is calculated to determine whether it is redundant or not. (2) A sensor node interacts with its neighbor nodes to decide the sleeping priority; A node exchanges sleep priority information with its neighbor node, so that to decide whether to sleep or not, so as to effectively avoid the occurrence of coverage hole. Simulation results show that, compared with the existing mod-LEACH algorithm, VSGCA algorithm and GAF algorithm, SGLE algorithm has a significant improvement in node survival rate, node mortality rate, network coverage rate and working node ratio under the same conditions.
