Mobility-Aware Workflow Offloading and Scheduling Strategy for Mobile Edge Computing

Abstract

Currently, Mobile Edge Computing (MEC) is widely used in different smart application scenarios such as smart health, smart traffic and smart home. However, smart end devices are usually constrained in battery and computing power, and hence how to optimize the energy consumption of end devices with intelligent task offloading and scheduling strategies under constraints such as deadlines is a critical yet challenging topic. Meanwhile, most existing studies do not consider the mobility of end devices during task execution but in reality end devices may need to be constantly moving in a MEC environment. In this paper, motivated by a patient health monitoring scenario, we propose a Mobility-Aware Workflow Offloading and Scheduling Strategy (MAWOSS) for MEC which provides a holistic approach that covers the workflow task offloading strategy, the workflow task scheduling algorithm and the workflow task migration strategy. Comprehensive experimental results show that compared with others, MAWOSS is able to achieve the optimal fitness with lower energy consumption and smaller workflow makespan under the deadlines.