Mobile edge computing can augment the capabilities of mobile terminals (MTs) by enabling computing and caching functionalities for base stations (BSs). Because BSs have only limited computation and storage resources compared with cloud servers, they need to efficiently manage the computation offloading and data caching for MTs. In this paper, a novel scheme for efficient computation offloading and data caching assisted by mobile-edge-computing–enabled BSs (MEC-BSs) is proposed. To maximize the MT benefits in terms of reduced time and energy consumption, our scheme determines the probability that each MT offloads each type of its tasks to the MEC-BS and indicates whether the cloud data for each type of MT task is cached at the MEC-BS. A balance factor is used to flexibly adjust the tendency of the optimization between the minimization of time and energy consumption. Based on the stable probabilistic characteristics of MT tasks and the MEC-BS service, the optimization algorithm of our scheme can be executed independently and concurrently without deteriorating the system performance. The simulation results demonstrate that our scheme can largely improve the system performance and that it always outperforms other reference schemes in scenarios with multiple criteria.

移动边缘计算可以通过启用基站（BS）的计算和缓存功能来增强移动终端（MT）的功能。由于BS与云服务器相比仅具有有限的计算和存储资源，因此它们需要有效地管理MT的计算分流和数据缓存。在本文中，提出了一种新的方案，该方案通过启用移动边缘计算的BS（MEC-BS）辅助进行高效的计算分流和数据缓存。为了在减少时间和能源消耗方面最大化MT收益，我们的方案确定每个MT将每种类型的任务卸载到MEC-BS的可能性，并指示每种MT任务的云数据是否已缓存在MEC上-BS。平衡因子用于灵活地在最小化时间和能耗之间调整优化趋势。基于MT任务和MEC-BS服务的稳定概率特性，我们的方案优化算法可以独立并发执行，而不会降低系统性能。仿真结果表明，我们的方案可以在很大程度上提高系统性能，并且在具有多个条件的情况下，其性能总是优于其他参考方案。