You Can Recharge With Detouring: Optimizing Placement for Roadside Wireless Charger

Wireless energy transfer technologies have played an important role in the development of Internet of Things. Most of the previous studies focus on scheduling mobile chargers efficiently for rechargeable sensor nodes. In this paper, we investigate the deployment problem for wireless charging station...

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Main Authors: Xunpeng Rao, Yubo Yan, Maotian Zhang, Wanru Xu, Xiaochen Fan, Hao Zhou, Panlong Yang
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8023965/
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spelling doaj-f42fec4468454d4f83b5ec17be7bde382021-03-29T20:31:17ZengIEEEIEEE Access2169-35362018-01-016475910.1109/ACCESS.2017.27412208023965You Can Recharge With Detouring: Optimizing Placement for Roadside Wireless ChargerXunpeng Rao0https://orcid.org/0000-0002-3083-3666Yubo Yan1Maotian Zhang2https://orcid.org/0000-0001-6406-8408Wanru Xu3https://orcid.org/0000-0003-0235-6978Xiaochen Fan4Hao Zhou5Panlong Yang6College of Communications Engineering, PLA University of Science and Technology, Nanjing, ChinaCollege of Communications Engineering, PLA University of Science and Technology, Nanjing, ChinaCollege of Communications Engineering, PLA University of Science and Technology, Nanjing, ChinaCollege of Communications Engineering, PLA University of Science and Technology, Nanjing, ChinaFEIT, School of Computing and Communications, University of Technology Sydney, Sydney, NSW, AustraliaSchool of Computer Science and Technology, University of Science and Technology of China, Hefei, ChinaSchool of Computer Science and Technology, University of Science and Technology of China, Hefei, ChinaWireless energy transfer technologies have played an important role in the development of Internet of Things. Most of the previous studies focus on scheduling mobile chargers efficiently for rechargeable sensor nodes. In this paper, we investigate the deployment problem for wireless charging stations (WCSs) in urban areas with respect to the users detouring cost when they move to the candidate WCSs. With pre-known user's trajectories and given number of WCSs, we deploy the WCSs to maximize the number of recharged users with guaranteed probability. We convert our deployment problem into an NP-hard weighted maximum coverage problem, and prove the objective function is a maximum submodular set function. To this end, a simple but efficient greedy algorithm with approximation factor of (1 - 1/ε) is proposed for the threshold detouring mode. In addition, an improved algorithm with an approximation factor of (1 - 1/√e) is presented for the linear/nonlinear detouring mode. Finally, we evaluate the performance of our algorithms by comparing them with two typical heuristic algorithms (flow-centric and random-based), and the impacts of different detouring thresholds on our algorithms by synthetic traces. Moreover, real trace-driven evaluations validate that our algorithm improves the coverage quality by 75% when compared to the two aforementioned algorithms.https://ieeexplore.ieee.org/document/8023965/Wireless energy transfercharger placementdetourapproximation algorithm
collection DOAJ
language English
format Article
sources DOAJ
author Xunpeng Rao
Yubo Yan
Maotian Zhang
Wanru Xu
Xiaochen Fan
Hao Zhou
Panlong Yang
spellingShingle Xunpeng Rao
Yubo Yan
Maotian Zhang
Wanru Xu
Xiaochen Fan
Hao Zhou
Panlong Yang
You Can Recharge With Detouring: Optimizing Placement for Roadside Wireless Charger
IEEE Access
Wireless energy transfer
charger placement
detour
approximation algorithm
author_facet Xunpeng Rao
Yubo Yan
Maotian Zhang
Wanru Xu
Xiaochen Fan
Hao Zhou
Panlong Yang
author_sort Xunpeng Rao
title You Can Recharge With Detouring: Optimizing Placement for Roadside Wireless Charger
title_short You Can Recharge With Detouring: Optimizing Placement for Roadside Wireless Charger
title_full You Can Recharge With Detouring: Optimizing Placement for Roadside Wireless Charger
title_fullStr You Can Recharge With Detouring: Optimizing Placement for Roadside Wireless Charger
title_full_unstemmed You Can Recharge With Detouring: Optimizing Placement for Roadside Wireless Charger
title_sort you can recharge with detouring: optimizing placement for roadside wireless charger
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2018-01-01
description Wireless energy transfer technologies have played an important role in the development of Internet of Things. Most of the previous studies focus on scheduling mobile chargers efficiently for rechargeable sensor nodes. In this paper, we investigate the deployment problem for wireless charging stations (WCSs) in urban areas with respect to the users detouring cost when they move to the candidate WCSs. With pre-known user's trajectories and given number of WCSs, we deploy the WCSs to maximize the number of recharged users with guaranteed probability. We convert our deployment problem into an NP-hard weighted maximum coverage problem, and prove the objective function is a maximum submodular set function. To this end, a simple but efficient greedy algorithm with approximation factor of (1 - 1/ε) is proposed for the threshold detouring mode. In addition, an improved algorithm with an approximation factor of (1 - 1/√e) is presented for the linear/nonlinear detouring mode. Finally, we evaluate the performance of our algorithms by comparing them with two typical heuristic algorithms (flow-centric and random-based), and the impacts of different detouring thresholds on our algorithms by synthetic traces. Moreover, real trace-driven evaluations validate that our algorithm improves the coverage quality by 75% when compared to the two aforementioned algorithms.
topic Wireless energy transfer
charger placement
detour
approximation algorithm
url https://ieeexplore.ieee.org/document/8023965/
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