Joint Optimization Scheme of Resource Allocation and Offloading Decision in Mobile Edge Computing

Abstract

Considering the problem of users high processing delay and energy consumption in mobile edge computing (MEC), a joint optimization scheme of resource allocation and offloading decision based on the “cloud-edge-end” three-tier MEC computation offloading structure is proposed. Firstly, considering the system delay and energy con-sumption, the optimization problem is studied in order to maximize the users task offloading gain, which is measured by a weighted sum of reductions in tasks relative processing delay and energy consumption. Secondly, the priority is set for users tasks and the offloading decision is initialized according to the data size of tasks. Then, the channel allocation algorithm that balances transmission performance is proposed to allocate channel resources for offloading tasks. For the tasks that are offloaded to the same edge server, the optimal allocation of computing resources can be achieved by computing for resources with the goal of maximizing resources profit. Finally, the optimization problem is proven to be a potential function about the offloading decision based on game theory, that is, there exists a Nash equilibrium, and the iterative method by comparing the gain value is used to achieve the offloading decision under Nash equilibrium. The simulation results show that the proposed joint optimization scheme achieves the maximum total system gain under meeting the processing delay requirements of users, and effectively improves the performance of computation offloading.

Keywords

• mobile edge computing (mec)
• resource allocation
• offloading decision
• potential game