Multiple Relays Assisted MEC System for Dynamic Offloading and Resource Scheduling with Energy Harvesting

Abstract

Mobile Edge Computing (MEC) has become an indispensable way to reduce the execution delay of devices. However, for some devices located far away from the MEC server, the transmission delay of communication with MEC is still large. In this case, we consider using multiple relay devices to assist Internet of Things (IoT) devices to communicate with MEC servers. To enhance the energy efficiency of the system, we introduce Energy Harvesting (EH) devices to provide energy for the IoT devices. Our objective is to maximize the utilization of EH devices while minimizing the overall delay in task offloading for the IoT devices. We tackle the problem by formulating it as a Markov Decision Problem (MDP). However, due to the significant expansion of the state space, traditional methods such as relative value iteration and linear iterative reconstruction are ineffective in solving this problem. Hence, we propose an approach called Multi-Relay Assisted Dynamic Computation Offloading (MRADCO) algorithm, which leverages the Lyapunov optimization technique. It is important to note that our proposed algorithm makes decisions solely based on the current state, without requiring the distribution information of the wireless channel and EH process. This characteristic enhances the algorithm’s practicality and reduces complexity in real-world implementations. Through rigorous theoretical derivation and comprehensive simulation experiments, we demonstrate that our algorithm is asymptotically optimal. And compared with the benchmark algorithm LODCO, our algorithm reduces the time by 50%.