He, H.; Zhou, C.; Huang, F.; Shen, H.; Li, S. Energy-Efficient Task Offloading in Wireless-Powered MEC: A Dynamic and Cooperative Approach. Preprints2024, 2024070056. https://doi.org/10.20944/preprints202407.0056.v1
APA Style
He, H., Zhou, C., Huang, F., Shen, H., & Li, S. (2024). Energy-Efficient Task Offloading in Wireless-Powered MEC: A Dynamic and Cooperative Approach. Preprints. https://doi.org/10.20944/preprints202407.0056.v1
Chicago/Turabian Style
He, H., Hong Shen and Shuangjuan Li. 2024 "Energy-Efficient Task Offloading in Wireless-Powered MEC: A Dynamic and Cooperative Approach" Preprints. https://doi.org/10.20944/preprints202407.0056.v1
Abstract
Mobile Edge Computing (MEC) integrated with Wireless Power Transfer (WPT) is emerging as a promising solution to reduce task delays and extend the battery life of Mobile Devices (MDs). Cooperative user communication, or relay technology, enhances communication efficiency for users located far from the base station by mitigating the double near-far effect caused by distance. This is considered a key technology in Beyond 5G (B5G) and future communication systems. In this paper, we focus on maximizing the long-term energy efficiency (EE) of a user-cooperation WPT-MEC system, while taking into account the uncertain load dynamics at the edge MD and the time-varying state of the wireless channel. The joint optimization of wireless charging time fraction, MD offloading duration, helper node processing time, and transfer power decision presents significant challenges due to the coupling of data offloading among cooperative users and a volatile system environment. To address these challenges, we formulate the problem as a stochastic programming problem and propose an online control algorithm, DOUCA, to solve it. Our approach utilizes Dinkelbach’s method and Lyapunov optimization theory to decouple the sequential decision problem into a deterministic sub-problem for each time slot. For the sub-problem, we use variable substitution to convert the non-convex problem into a convex one, containing only a small number of variables, which can be efficiently solved. Furthermore, we provide a mathematical analysis of our algorithm’s performance. Extensive simulation results demonstrate the effectiveness of our proposed algorithm, as evidenced by an impressive energy efficiency improvement of over 20% compared to benchmark methods. Our algorithm also achieves a trade-off between EE and system stability.
Keywords
Mobile edge computing(MEC); wireless power transfer(WPT); user cooperation; Lyapunov optimization; convex optimization
Subject
Computer Science and Mathematics, Computer Networks and Communications
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
