Abstract:

Mobile edge computing (MEC) emerges as a new paradigm that pushes the computing infrastructure from the remote cloud data center to the edge equipments.It provides a new solution to meet the delay sensitive and computing intensive requirements of Internet of things (IoT).In this work, the problem of tasks offloading and scheduling in the multi-user and multi-server MEC system was considered.Specifically, each user had a task-dependent application and the tasks could be either executed locally or remotely according to the dependence.Thus, the network performance was improved by unloading and scheduling the sub tasks.Quality of experience (QoE) and fairness between users were used to characterize the network performance, and the optimization problem was modeled as a joint dependent task offloading and scheduling (J-DTOS) problem.The J-DTOS problem was a non-linear mixed integer programming, which was NP-hard in general.The original problem was reformulated by introducing intermediate variables and proposing a near-optimal solution.Simulation results show that the proposed offloading and scheduling design can significantly improve the performance of the system.

Key words: Internet of things, mobile edge computing, dependent task offloading