A Game-Theoretical Approach for Energy-Efficient Resource Allocation in MEC Network

Mobile edge computing (MEC) is a promising technique which enables the user equipment (UE) to leverage the vast computation resources on the clouds (or cloudlets). The redundant design and dynamic nature of traffic raise an energy inefficiency issue in MEC network. In this paper, we aim to minimize the energy consumption and average response time in the MEC network. We jointly consider the cloud selection and routing optimization on both wired and wireless links. Based on the game theory, we propose a low-complex resource allocation algorithm, which can achieve the global optimal solution. Further, to reduce the number of re-routing (routing times), an improved algorithm is proposed, which introduces an approximate factor (i.e., β). The β represents the additional cost during the re-routing, such as session migrations, energy consumption. We demonstrate the convergence of the improved algorithm. The simulations show that the proposed algorithms outperform the other conventional algorithms.