Latency-Oblivious Distributed Task Scheduling for Mobile Edge Computing

Abstract

Mobile Edge Computing (MEC) is emerging as one of the effective platforms for offloading the resource- and latency-constrained computational services of modern mobile applications. For latency- and resource-constrained mobile devices, the important issues include: 1) minimize end-to-end service latency; 2) minimize service completion time; 3) high quality-of-service (QoS) requirement to offload the complex computational services. To address the above issues, a latency-oblivious distributed task scheduling scheme is designed in this work to maximize the QoS performance and goodput for the MEC services. Unlike most of the existing works, we consider the latency-oblivious property of different services in order to achieve the optimized goodput and service latency. Furthermore, we design an optimal decision engine for efficiently offloading the computational services. Simulation results are presented to demonstrate the effectiveness of the proposed offloading scheme over other existing state-of-the-art solutions, in terms of service latency, goodput, service completion time and fairness.