Title | ||
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RCSS: A Real-Time On-Demand Charging Scheduling Scheme for Wireless Rechargeable Sensor Networks. |
Abstract | ||
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With the emergence of edge computing, a large number of devices such as sensor nodes have been deployed in the edge network to sense and process data. However, how to provide real-time on-demand energy for these edge devices is a new challenge issue of edge networks. In real-world applications of edge computing, sensor nodes usually have different task burdens due to the environmental impact, which results in a dynamic change of the energy consumption rate at different nodes. Therefore, the traditional periodical charging mode cannot meet the nodes charging demand that have dynamic energy consumption. In this paper, we propose a real-time on-demand charging scheduling scheme (RCSS) under the condition of limited mobile charger capacity. In the process of building the charging path, RCSS adequately considers the dynamic energy consumption of different node, and puts forward the next node selection algorithm. At the same time, a method to determine the feasibility of charging circuit is also proposed to ensure the charging efficiency. During the charging process, RCSS is based on adaptive charging threshold to reduce node mortality. Compared with existing approaches, the proposed RCSS achieves better performance in the number of survival nodes, the average service time and charging efficiency. |
Year | DOI | Venue |
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2018 | 10.3390/s18051601 | SENSORS |
Keywords | Field | DocType |
adaptive charging threshold,energy consumption rate,on-demand charging scheduling,wireless rechargeable sensor networks (WRSNs) | Edge computing,Wireless,Scheduling (computing),Selection algorithm,Enhanced Data Rates for GSM Evolution,Electronic engineering,Real-time computing,Edge device,Engineering,Energy consumption,Wireless sensor network | Journal |
Volume | Issue | Citations |
18 | 5.0 | 7 |
PageRank | References | Authors |
0.46 | 17 | 5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Ping Zhong | 1 | 28 | 4.89 |
Yiwen Zhang | 2 | 28 | 5.81 |
Shuaihua Ma | 3 | 7 | 0.80 |
Xiaoyan Kui | 4 | 69 | 12.54 |
Jianliang Gao | 5 | 106 | 20.98 |