SCAPE: Safe Charging with Adjustable Power

Haipeng Dai; Yunhuai Liu; Guihai Chen; Xiaobing Wu; Tian He; Alex X. Liu; Yang Zhao

doi:10.1109/TNET.2018.2793949

SCAPE: Safe Charging with Adjustable Power

Haipeng Dai, Yunhuai Liu, Guihai Chen, Xiaobing Wu, Tian He, Alex X. Liu, Yang Zhao

Computer Science and Engineering

Research output: Contribution to journal › Article › peer-review

69 Scopus citations

Abstract

Wireless power transfer technology is considered as one of the promising solutions to address the energy limitation problems for end-devices, but its incurred potential risk of electromagnetic radiation (EMR) exposure is largely overlooked by most existing works. In this paper, we consider the Safe Charging with Adjustable PowEr (SCAPE) problem, namely, how to adjust the power of chargers to maximize the charging utility of devices, while assuring that EMR intensity at any location in the field does not exceed a given threshold R-{t}. We present novel techniques to reformulate SCAPE into a traditional linear programming problem, and then remove its redundant constraints as much as possible to reduce computational effort. Next, we propose a series of distributed algorithms, including a fully distributed algorithm that provably achieves (1-ϵ) approximation ratio and requires only communications with neighbors within a constant distance for each charger. Through extensive simulation and testbed experiments, we demonstrate that our proposed algorithms can outperform the set-cover algorithm by up to 17.05%, and has an average performance gain of 41.1% over the existing algorithm in terms of the overall charging utility.

Original language	English (US)
Pages (from-to)	520-533
Number of pages	14
Journal	IEEE/ACM Transactions on Networking
Volume	26
Issue number	1
DOIs	https://doi.org/10.1109/TNET.2018.2793949
State	Published - Feb 2018

Bibliographical note

Funding Information:
Manuscript received December 25, 2016; revised October 5, 2017; accepted December 13, 2017; approved by IEEE/ACM TRANSACTIONS ON NET-WORKING Editor M. Chen. Date of publication January 31, 2018; date of current version February 14, 2018. This work was supported in part by the National Natural Science Foundation of China under Grant 61502229, Grant 61672353, Grant 61472252, Grant 61321491, Grant 61332018, Grant 61772046, Grant 61629302, Grant 61373130, Grant 61672276, and Grant 61472184, in part by the China 973 projects under Grant 2014CB340303, in part by the Joint Research Fund for Overseas Chinese Scholars and Scholars in Hong Kong and Macao Young Scholars under Grant F030307, in part by the National Science Foundation under Grant CNS-1318563, Grant CNS-1524698, and Grant CNS-1421407, in part by the IIP under Grant 1632051, and in part by the Jiangsu High-level Innovation and Entrepreneurship (Shuangchuang) Program. (Corresponding authors: Yunhuai Liu; Guihai Chen; Tian He.) H. Dai, G. Chen, and Y. Zhao are with the State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023, China (e-mail: [email protected]; [email protected]; [email protected]).

Publisher Copyright:
© 1993-2012 IEEE.

Keywords

Electromagnetic radiation
distributed algorithm
optimization
wireless power transfer

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10.1109/TNET.2018.2793949

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title = "SCAPE: Safe Charging with Adjustable Power",

abstract = "Wireless power transfer technology is considered as one of the promising solutions to address the energy limitation problems for end-devices, but its incurred potential risk of electromagnetic radiation (EMR) exposure is largely overlooked by most existing works. In this paper, we consider the Safe Charging with Adjustable PowEr (SCAPE) problem, namely, how to adjust the power of chargers to maximize the charging utility of devices, while assuring that EMR intensity at any location in the field does not exceed a given threshold R-{t}. We present novel techniques to reformulate SCAPE into a traditional linear programming problem, and then remove its redundant constraints as much as possible to reduce computational effort. Next, we propose a series of distributed algorithms, including a fully distributed algorithm that provably achieves (1-ϵ) approximation ratio and requires only communications with neighbors within a constant distance for each charger. Through extensive simulation and testbed experiments, we demonstrate that our proposed algorithms can outperform the set-cover algorithm by up to 17.05%, and has an average performance gain of 41.1% over the existing algorithm in terms of the overall charging utility.",

keywords = "Electromagnetic radiation, distributed algorithm, optimization, wireless power transfer",

author = "Haipeng Dai and Yunhuai Liu and Guihai Chen and Xiaobing Wu and Tian He and Liu, {Alex X.} and Yang Zhao",

note = "Funding Information: Manuscript received December 25, 2016; revised October 5, 2017; accepted December 13, 2017; approved by IEEE/ACM TRANSACTIONS ON NET-WORKING Editor M. Chen. Date of publication January 31, 2018; date of current version February 14, 2018. This work was supported in part by the National Natural Science Foundation of China under Grant 61502229, Grant 61672353, Grant 61472252, Grant 61321491, Grant 61332018, Grant 61772046, Grant 61629302, Grant 61373130, Grant 61672276, and Grant 61472184, in part by the China 973 projects under Grant 2014CB340303, in part by the Joint Research Fund for Overseas Chinese Scholars and Scholars in Hong Kong and Macao Young Scholars under Grant F030307, in part by the National Science Foundation under Grant CNS-1318563, Grant CNS-1524698, and Grant CNS-1421407, in part by the IIP under Grant 1632051, and in part by the Jiangsu High-level Innovation and Entrepreneurship (Shuangchuang) Program. (Corresponding authors: Yunhuai Liu; Guihai Chen; Tian He.) H. Dai, G. Chen, and Y. Zhao are with the State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023, China (e-mail: [email protected]; [email protected]; [email protected]). Publisher Copyright: {\textcopyright} 1993-2012 IEEE.",

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N2 - Wireless power transfer technology is considered as one of the promising solutions to address the energy limitation problems for end-devices, but its incurred potential risk of electromagnetic radiation (EMR) exposure is largely overlooked by most existing works. In this paper, we consider the Safe Charging with Adjustable PowEr (SCAPE) problem, namely, how to adjust the power of chargers to maximize the charging utility of devices, while assuring that EMR intensity at any location in the field does not exceed a given threshold R-{t}. We present novel techniques to reformulate SCAPE into a traditional linear programming problem, and then remove its redundant constraints as much as possible to reduce computational effort. Next, we propose a series of distributed algorithms, including a fully distributed algorithm that provably achieves (1-ϵ) approximation ratio and requires only communications with neighbors within a constant distance for each charger. Through extensive simulation and testbed experiments, we demonstrate that our proposed algorithms can outperform the set-cover algorithm by up to 17.05%, and has an average performance gain of 41.1% over the existing algorithm in terms of the overall charging utility.

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SCAPE: Safe Charging with Adjustable Power

Abstract

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