Enhanced Lyapunov Optimization of MEC Offload for Energy Harvesting Devices

Mobile Edge Computing (MEC) system can provide data offloading services at the network edge to cope with the growing computing needs in smart grid networks. This greatly reduces end-to-end latency and device energy consumption to enhance user Quality of Experience (QoE). However, due to the limited battery life on the terminal device, when the battery energy is exhausted, the calculation will be interrupted. In order to achieve relatively green computing and have excellent computing performance, it is particularly important to provide renewable energy for devices through energy harvesting (EH). Therefore, this paper is aimed at a MEC system with EH equipment, combined with an efficient computing offload tactic, using the execution cost as the performance index. The Lyapunov Optimization-based Dynamic Computation Offloading (LODCO) algorithm for multi-user and multi-server mobile edge computing system in smart grids is updated and re-factored, and the execution mode of every mobile device is chosen to reduce implementation cost. At last, simulation results validate the proposed algorithm. It is shown that the improved LODCO algorithm not only inherits all the merits of LODCO, but also increases the computation load ratio and reduces the execution cost. This is more suitable for smart grid systems with fixed terminals and mobile terminals at the same time, making them more efficient and stable.