QoE and Reliability-Aware Task Scheduling for Multi-user Mobile-Edge Computing

Mobile-edge computing (MEC) has become a popular research topic from both academia and industry since it can alleviate the computation and power limitations of mobile devices by offloading computation-intensive and energy-consuming tasks from mobile users to nearby edge servers for remote execution. Existing papers have studied related problems, however, none of them considers the reliability of MEC systems that may suffer soft errors during execution and bit errors during offloading. In this work, we study the task offloading and scheduling problem targeting to maximize the quality of experience (QoE) of multi-user MEC systems under a certain reliability requirement. We propose to decompose the original problem into i) a task offloading optimization problem, ii) a task-to-server assignment problem for ensuring system reliability constraint, and iii) a computing resource allocation problem for maximizing system QoE. To address these sub-problems, we first obtain the optimal offloading decision using the discrete particle swarm optimization method. We then propose a reliability-optimality analysis-based task assignment heuristic and a utility-optimal resource allocation algorithm. Simulation results show that our scheme outperforms two state-of-the-art approaches and two baseline methods. The average improvement on QoE (quantified by offloading utility) achieved by our scheme is up to 63.2% under reliability requirement.