Distributed Energy Saving for Heterogeneous Multi-layer Mobile Edge Computing

In this paper, we consider the distributed energy saving for heterogeneous multi-layer mobile edge computing (HetMEC), where the edge devices (EDs) upload computing tasks to the mobile edge computing (MEC) servers and the cloud center (CC) for processing. To reduce the energy consumption, task offloading and resource allocation are performed by each device independently to distribute the computation load. However, due to the partial information, the offloading strategies of devices on different layers can hardly be aligned, which may lead to network congestion. To address this problem, we propose a smart pricing mechanism to coordinate the strategies of multi-layer devices, where the CC charges the MEC servers and EDs for computing services and network congestion. The pricing based distributed task offloading and resource allocation algorithm is designed to minimize the total energy consumption subject to latency requirements. Simulation results indicate that our algorithm achieves lower energy consumption and congestion probability compared with the traditional distributed method.