A Delay and Energy-Aware Task Offloading and Resource Optimization in Mobile Edge Computing

Abstract

The rapid development and diffusion of the Internet of Things (IoT) have increased the growth of smart devices (SDs). SDs may run computation-intensive and delay-sensitive applications. However, SDs with limited computation power and a small battery cannot execute these applications. To solve this problem, task offloading can be used to transfer compute-intensive tasks to an external server or processor in mobile edge computing (MEC). There are many studies on task offloading or resource allocation in MEC systems, but few researches consider selecting an appropriate edge node (EN) as the optimal cost. In this paper, we propose an MEC system to minimize SDs’ delay and energy consumption costs by offloading tasks to the adjacent ENs. We compared our proposed method with currently used techniques. The simulation results demonstrate the effectiveness of this proposed algorithm in terms of the delay cost and energy costs.