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http://dx.doi.org/10.3837/tiis.2018.12.001

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

Liu, Peng (College of Computer Science and Technology, Jilin University)
Xu, Gaochao (College of Computer Science and Technology, Jilin University)
Yang, Kun (School of Computer Science and Electronic Engineering, University of Essex)
Wang, Kezhi (Department of Computer and Information Sciences Northumbria University)
Li, Yang (College of Computer Science and Technology, Jilin University)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.12, no.12, 2018 , pp. 5614-5633 More about this Journal
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 efficiency.
Keywords
mobile edge computing; wireless power transfer; joint optimization; convex optimization; BFGS;
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