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Status已发表Published
TitleTask-driven charger placement and power allocation for wireless sensor networks
Creator
Date Issued2021-08-01
Source PublicationAd Hoc Networks
ISSN1570-8705
Volume119
Abstract

Deploying wireless chargers is a promising way to provide continuous energy supply for battery-driven sensor nodes, and has attracted more and more attention recently. Existing works mainly focus on studying the charging utility maximization problem, that is, they aim to supply as much power as possible to all sensor nodes with a certain number of wireless chargers. However, these works ignore the task performing function of sensor nodes, supplying more power to sensor nodes cannot guarantee that tasks can be performed better. In this paper, therefore, we consider a more practical issue of deploying wireless chargers, where our objective is to maximize the total achieved task utility with a limited deployment cost budget. We formulate our problem as a mixed integer non-linear programming problem, and prove its NP-Hardness. To address this problem, we split it into two sub-problems, where the first sub-problem is about power allocation for sensor nodes, and the second sub-problem is about optimal wireless charger placement. We design an approximation algorithm for each sub-problem, and give theoretical analyses of our algorithms. By solving the two sub-problems accordingly, we get a feasible solution that has a [Fromula Presented] performance guarantee for the original problem. Finally, we conduct extensive simulations to validate the performance of our algorithms. The results show that our designs significantly outperform the baseline algorithms, which demonstrates the effectiveness of our algorithms.

KeywordCharging power allocation Optimal charger placement Task utility Wireless charger
DOI10.1016/j.adhoc.2021.102556
URLView source
Indexed BySCIE
Language英语English
WOS Research AreaComputer Science ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Telecommunications
WOS IDWOS:000661871100002
Scopus ID2-s2.0-85110444026
Citation statistics
Cited Times:10[WOS]   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/9093
CollectionResearch outside affiliated institution
Corresponding AuthorLi, Deying
Affiliation
1.School of Software Engineering,Beijing University of Technology,Beijing,100124,China
2.School of Information,Renmin University of China,Beijing,100872,China
3.Department of Computer Science,Erik Jonsson School of Engineering and Computer Science,University of Texas at Dallas,Richardson,75080,United States
Recommended Citation
GB/T 7714
Ding, Xingjian,Guo, Jianxiong,Wang, Yongcaiet al. Task-driven charger placement and power allocation for wireless sensor networks[J]. Ad Hoc Networks, 2021, 119.
APA Ding, Xingjian, Guo, Jianxiong, Wang, Yongcai, Li, Deying, & Wu, Weili. (2021). Task-driven charger placement and power allocation for wireless sensor networks. Ad Hoc Networks, 119.
MLA Ding, Xingjian,et al."Task-driven charger placement and power allocation for wireless sensor networks". Ad Hoc Networks 119(2021).
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