Integrated Task Caching, Computation Offloading and Resource Allocation for Mobile Edge Computing

Abstract

Applications with more sensitive delay and larger data volumes, such as interactive gaming and augmented reality, have become popular recently. Computation offloading is expected as a promising technique to meet low latency for mobile users. However, computation offloading requires communication between mobile users and the mobile edge computing (MEC) server, the delay and energy consumption caused by the transmission are considerable expenses for users. Motivated by this, we consider joint computation offloading and task caching optimization in a cellular network where users can proactively cache and offload their tasks at the MEC server. The objective of this paper is to minimize the system cost, which is defined as the weighted sum of task execution delay and energy consumption for all users. By formulating the problem as mixed-integer non-linear programming, we propose to find the optimal solution by three steps. Through which we have obtained the optimal computing resource allocation, the optimal task caching scheme and an algorithm which yields the optimal computation offloading scheme. Simulation results show that in comparison to the other three benchmark methods, the proposed scheme can effectively reduce the system cost.