Decentralized Computation Offloading and Resource Allocation for Mobile-Edge Computing: A Matching Game Approach

Abstract

In this paper, we propose an optimization framework of computation offloading and resource allocation for mobile-edge computing with multiple servers. Concretely, we aim to minimize the system-wide computation overhead by jointly optimizing the individual computation decisions, transmit power of the users, and computation resource at the servers. The crux of the problem lies in the combinatorial nature of multi-user offloading decisions, the complexity of the optimization objective, and the existence of inter-cell interference. To overcome these difficulties, we adopt a suboptimal approach by splitting the original problem into two parts: 1) computation offloading decision and 2) joint resource allocation. To enable distributed computation offloading, two matching algorithms are investigated. Moreover, the transmit power of offloading users is found using a bisection method with approximate inter-cell interference, and the computation resources allocated to offloading users is achieved via the duality approach. Simulation results validate that the proposed framework can significantly improve the percentage of offloading users and reduce the system overhead with respect to the existing schemes. Our results also show that the proposed framework performs close to the centralized heuristic algorithm with a small optimality gap.

Keywords

• Heterogeneous networks
• matching theory
• mobile edge computing
• resource allocation