Joint task offloading and data caching in mobile edge computing networks

Mobile edge computing (MEC) provides more computing and storage capability for the network edge devices to meet the latency-critical mobile applications running in mobile terminals. However, the computation/storage resource at the edge servers are limited, and only the important application data can be cached in the edge server. Thus, it is necessary to figure out the wise caching decision to minimize edge computing latency and energy consumption. This paper considers a system in which most mobile devices migrate duplicate computation tasks to the edge servers and share the data contents requested for computation tasks. To reduce the overall latency of all mobile devices, we study the collaborative task offloading and data caching models. In addition, we propose an efficient Lyapunov online algorithm that can perform joint task offloading and dynamic data caching strategies for computation tasks or data contents. The simulation results show that the proposed algorithm outperforms the traditional strategy in task offloading and data caching, which can effectively decrease the overall service latency of all mobile devices.