Research Area:  Edge Computing

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). However, maximizing the long-term energy efficiency (EE) of a user-cooperative WPT-MEC system presents significant challenges due to uncertain load dynamics at the edge MD and the time-varying state of the wireless channel. In this paper, we propose an online control algorithm to maximize the long-term EE of a WPT-MEC system by making decisions on time allocations and transmission powers of mobile devices (MDs) for a three-node network. We formulate a stochastic programming problem considering the stability of network queues and time-coupled battery levels. By leveraging Dinkelbach’s method, we transform the fractional optimal problem into a more manageable form and then use the Lyapunov optimization technique to decouple the problem into a deterministic optimization problem for each time slot. For the sub-problem in each time slot, we use the variable substitution technique and convex optimization theory to convert the non-convex problem into a convex problem, which can be solved efficiently. Extensive simulation results demonstrate that our proposed algorithm outperforms baseline algorithms, achieving a 20% improvement in energy efficiency. Moreover, our algorithm achieves an [𝑂(1/𝑉),𝑂(𝑉)] trade-off between EE and network queue stability.

Keywords:  

Author(s) Name:  Huaiwen He,Chenghao Zhou,Feng Huang,Hong Shen and Shuangjuan Li

Publisher name:  ResearchGate

DOI:  10.20944/preprints202407.0056.v1

Volume Information:  Volume 221,(2024)

Paper Link:   https://www.researchgate.net/publication/381928897_Energy-Efficient_Task_Offloading_in_Wireless-Powered_MEC_A_Dynamic_and_Cooperative_Approach