MEC-enabled Energy Cooperation for Sustainable 5G Networks Exploiting the Location Service API

TL;DR

This paper proposes an energy cooperation framework for sustainable 5G networks using MEC and energy harvesting, employing an online Lyapunov optimization algorithm to efficiently manage energy transfer based on location services.

Contribution

It introduces a novel joint energy allocation and routing algorithm leveraging MEC's Location Service API for green energy cooperation in 5G networks.

Findings

Lyapunov algorithm effectively manages energy transfer under normal solar conditions.

Energy cooperation reduces reliance on the power grid and enhances sustainability.

The approach adapts to energy variations within the network.

Abstract

The substantial growth in wireless data traffic, and the emergence of delay-sensitive application/services requiring ultra-low latency, has resulted into a new Mobile Network (MN) design paradigm called Multi-access Edge Computing (MEC). In this, the Base Stations (BSs) are empowered with computing capabilities, and they are densely deployed in order to increase network coverage and provide high throughput to mobile users. These developments require energy self-sustainability in order to minimize the carbon emission into the atmosphere and the dependence on the power grid. As a solution to this, we advocate for the integration of Energy Harvesting (EH) systems, e.g., solar panels or wind turbines (together with energy storage devices), into future BSs and edge computing systems (i.e., MEC servers). However, due to traffic load and harvested energy variations within a coverage area, the stored energy levels will also vary. To compensate for green energy imbalance within the network, energy cooperation (transfer) can be enabled by an energy trading application hosted in the MEC platform, and the energy packets traverse over the Power Packet Grid (DC power lines and switches) from the source BS(s) to the energy-deficient BS(s). In this paper, we jointly perform energy allocation and energy routing using an online algorithm based on Lyapunov drift-and-penalty optimization theorem (named Lyapunov) for enabling energy cooperation, leveraging the MEC Location Service (LS) Application Programmable Interface (API). Our numerical results reveal that the Lyapunov algorithm is able to deliver sufficient amount of energy under normal solar irradiance without the effects of the control parameter