NBS-Based Mobile Edge Computing: A Joint Optimization of QoS and Energy in Computation Offloading

Zhihao Peng, Guocheng Liao

Abstract: Integrating Mobile Edge Computing (MEC) into the Internet of Things (IoT) enables IoT devices with limited computational power and energy to offload their compute-intensive and latency-sensitive tasks to the edge of the network, thus providing high-quality services to the users. In this paper, we utilize Nash Bargaining Solution (NBS) to jointly optimize computation power scheduling and benefit sharing among edge devices efficiently and fairly. We decouple the NBS into task scheduling, computation power allocation and benefit sharing problem, and solve them with Alternating Direction Method of Multipliers (ADMM) algorithm and subgradient descent method. Numerical results validate our analysis and show that our proposed scheme significantly improves the energy efficiency of MEC in IoT networks compared to existing benchmarks.