Joint computation and communication resource allocation in mobile-edge cloud computing networks

Mobile devices are in general resource-constrained, having limited computation resource and battery life. It is a significant challenge to resolve the contradiction between resource-hungry applications and resource-constrained mobile devices. As a promising approach to address such a challenge, computation offloading enables mobile users to offload computation to nearby resource-rich cloud infrastructure to reduce energy consumption and improve performance. In this paper, we formulate the computation offloading decision making problem as a MEC server selection problem, considering how to find one proper MEC server for one user that carrying computation job. We propose a joint computation and communication resource allocation model. In this model, we consider both transmitting energy consumption and communication delay as communication cost in a multi-user and multi-MEC server scenario. We use two algorithms to solve the proposed model. One is Hungarian algorithm based MEC server selection algorithm, but it ignores the fairness of the system. Another is Fairness based MEC server selection algorithm, which incorporate the fairness of the system. Finally, we show the numerical simulation result.