Resource Allocation and Offloading Strategy in Mobile Edge Computing Considering Mobility and Inter-user Relevance

Abstract

Mobile edge computing (MEC) offloads tasks to the MEC server located at the edge of the network, which can not only solve intensive computing but also can ensure computation with low latency. In the research of MEC, there are few research on user mobility and inter-user relevance. In this paper, we consider the task computing of relevant users in the mobile process. We combine MEC with local computing to minimize the weighted sum of user's delay and energy consumption. First, we propose a joint optimization problem of offloading strategy and resource allocation. Then, we design an iterative algorithm based on the one-time offloading principle and delay constraints, according to the inter-user relevance and user mobility. We adopt a dichotomy to achieve resource allocation and obtain the optimal solution of the objective function. The experimental results show that the proposed iterative offloading algorithm can effectively reduce the delay and energy consumption when considering the relevance and mobility of users.