Power Optimization in Wireless Powered Based Mobile Edge Computing

Xiaohan Xu; Qibin Ye; Weidang Lu; Hong Peng; Bo Li

Machine Learning and Intelligent Communications. 4th International Conference, MLICOM 2019, Nanjing, China, August 24–25, 2019, Proceedings

Research Article

Power Optimization in Wireless Powered Based Mobile Edge Computing

Download

61 downloads

Cite: BibTeX Plain Text

@INPROCEEDINGS{10.1007/978-3-030-32388-2_16,
    author={Xiaohan Xu and Qibin Ye and Weidang Lu and Hong Peng and Bo Li},
    title={Power Optimization in Wireless Powered Based Mobile Edge Computing},
    proceedings={Machine Learning and Intelligent Communications. 4th International Conference, MLICOM 2019, Nanjing, China, August 24--25, 2019, Proceedings},
    proceedings_a={MLICOM},
    year={2019},
    month={10},
    keywords={Mobile edge computing User cooperation Wireless power transfer},
    doi={10.1007/978-3-030-32388-2_16}
}

Xiaohan Xu
Qibin Ye
Weidang Lu
Hong Peng
Bo Li
Year: 2019
Power Optimization in Wireless Powered Based Mobile Edge Computing
MLICOM
Springer
DOI: 10.1007/978-3-030-32388-2_16

Xiaohan Xu¹, Qibin Ye¹, Weidang Lu¹^,*, Hong Peng¹^,*, Bo Li²^,*

1: Zhejiang University of Technology
2: Harbin Institute of Technology

*Contact email: luweid@zjut.edu.cn, ph@zjut.edu.cn, libo1983@hit.edu.cn

Abstract

Mobile edge computing (MEC) can meet the requirements of high-bandwidth and low delay commanded by the boost developing of mobile network and shorten the network load. This paper investigates a wireless powered MEC system consists a single antenna AP, and two single antenna mobile devices, which are powered by wireless power transmissions (WPT) from AP. In order to settle the users’ near-far influence, the system will let the mobile devices closer from the AP mobile devices as a relay for unloading. The Objective of this paper is to minimize the transmission energy of the AP, taking into account the restraints of the computing task. Our solution is divided into two steps: first, the mathematical model of the problem is listed, and then the optimal solution of each feasible scheme is discussed in a classified manner, and the minimum transmission power of AP is obtained through comparison. Simulation results show that collaboration can reduce energy consumption and improve the user performance.

Keywords: Mobile edge computing User cooperation Wireless power transfer

Published: 2019-10-28
Appears in: SpringerLink

: http://dx.doi.org/10.1007/978-3-030-32388-2_16