An Online Scheduling Algorithm for Energy Minimization in Wireless Powered Mobile Edge Computing Networks

TL;DR

This paper proposes an online algorithm for energy-efficient resource scheduling in Wireless Powered Mobile Edge Computing networks, optimizing WPT and computation offloading to extend device lifetime.

Contribution

It introduces a novel Lyapunov-based online algorithm that jointly optimizes resource allocation in WP-MEC networks, reducing complexity and improving energy efficiency.

Findings

The algorithm effectively minimizes energy consumption in WP-MEC networks.

Simulation results show improved energy efficiency and feasible solutions.

The approach adapts to dynamic network conditions in real-time.

Abstract

The integration of Mobile Edge Computing (MEC) and Wireless Power Transfer (WPT), which is usually referred to as Wireless Powered Mobile Edge Computing (WP-MEC), has been recognized as a promising technique to enhance the lifetime and computation capacity of wireless devices (WDs). Compared to the conventional battery-powered MEC networks, WP-MEC brings new challenges to the computation scheduling problem because we have to jointly optimize the resource allocation in WPT and computation offloading. In this paper, we consider the energy minimization problem for WP-MEC networks with multiple WDs and multiple access points. We design an online algorithm by transforming the original problem into a series of deterministic optimization problems based on the Lyapunov optimization theory. To reduce the time complexity of our algorithm, the optimization problem is relaxed and decomposed into several independent subproblems. After solving each subproblem, we adjust the computed values of variables to obtain a feasible solution. Extensive simulations are conducted to validate the performance of the proposed algorithm.