Mobile Edge Computing (MEC) is critical to the development of the Internet of things (IoTs) and 5G networks. However, the computation and communication resources of edge servers are limited, so it is challenging to perform resource allocation especially when the competition among edge servers is also taken into consideration. In this paper, we propose a trading model to investigate both the computation and communication resources allocation in MEC systems with multi-server and multi-user. We model the dynamic behavior of mobile users (MUs) using an evolutionary game, and then we build the deterministic and stochastic models to study the evolution of MUs where the evolutionary equilibrium is considered as the solution. We propose an evolution algorithm to obtain the evolutionary equilibrium. Furthermore, we analyze the competition among edge cloud servers (ECSs) by a noncooperative game, and propose an iteration algorithm to obtain Nash equilibrium where the ECSs can adjust the amount of resources provided to MUs and the corresponding price charged in order to attract more MUs. The existences of evolutionary equilibrium and Nash equilibrium are validated in performance evaluation.

移动边缘计算（MEC）对于物联网（IoT）和5G网络的发展至关重要。然而，边缘服务器的计算和通信资源是有限的，因此执行资源分配具有挑战性，尤其是在还考虑了边缘服务器之间的竞争时。在本文中，我们提出了一个交易模型来研究具有多服务器和多用户的MEC系统中的计算和通信资源分配。我们使用演化博弈模型对移动用户（MU）的动态行为进行建模，然后建立确定性和随机模型来研究MU（以演化均衡为解决方案）的演化。我们提出了一种进化算法来获得进化均衡。此外，我们通过非合作博弈分析了边缘云服务器（ECS）之间的竞争，并提出了一种迭代算法来获得Nash均衡，其中ECS可以调整提供给MU的资源数量和相应的价格以吸引更多MU。绩效评估验证了演化均衡和纳什均衡的存在。