Joint Optimization for Residual Energy Maximization in Wireless Powered Mobile-Edge Computing Systems

Peng Liu, Gaochao Xu, Kun Yang, Kezhi Wang, Yang Li

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

Mobile Edge Computing (MEC) and Wireless Power Transfer (WPT) are both recognized as promising techniques, one is for solving the resource insufficient of mobile devices and the other is for powering the mobile device. Naturally, by integrating the two techniques, task will be capable of being executed by the harvested energy which makes it possible that less intrinsic energy consumption for task execution. However, this innovative integration is facing several challenges inevitably. In this paper, we aim at prolonging the battery life of mobile device for which we need to maximize the harvested energy and minimize the consumed energy simultaneously, which is formulated as residual energy maximization (REM) problem where the offloading ratio, energy harvesting time, CPU frequency and transmission power of mobile device are all considered as key factors. To this end, we jointly optimize the offloading ratio, energy harvesting time, CPU frequency and transmission power of mobile device to solve the REM problem. Furthermore, we propose an efficient convex optimization and sequential unconstrained minimization technique based combining method to solve the formulated multi-constrained nonlinear optimization problem. The result shows that our joint optimization outperforms the single optimization on REM problem. Besides, the proposed algorithm is more efficient.
Original languageEnglish
Pages (from-to)5614-5633
JournalKSII Transactions on Internet and Information Systems
Volume12
Issue number12
DOIs
Publication statusPublished - 31 Dec 2018

Fingerprint Dive into the research topics of 'Joint Optimization for Residual Energy Maximization in Wireless Powered Mobile-Edge Computing Systems'. Together they form a unique fingerprint.

Cite this