Online Service Provisioning and Updating in QoS-aware Mobile Edge Computing

The vigorous development of IoT technology has spawned a series of applications that are delay-sensitive or resource-intensive. Mobile edge computing is an emerging paradigm which provides services between end devices and traditional cloud data centers to users. However, with the continuously increasing investment of demands, it is nontrivial to maintain a higher quality-of-service (QoS) under the erratic activities of mobile users. In this paper, we investigate the service provisioning and updating problem under the multiple-users scenario by improving the performance of services with long-term cost constraints. We first decouple the original long-term optimization problem into a per-slot deterministic one by using Lyapunov optimization. Then, we propose two service updating decision strategies by considering the trajectory prediction conditions of users. Based on that, we design an online strategy by utilizing the committed horizon control method looking forward to multiple slots predictions. We prove the performance bound of our online strategy theoretically in terms of the trade-off between delay and cost. Extensive experiments demonstrate the superior performance of the proposed algorithm.

I. Introduction

The vigorous development of Internet of things (IoT) tech-nology has led to the explosive growth of mobile terminal equipment and data volume. At the same time, a series of resource-intensive and delay-sensitive applications, such as augmented reality (AR)/virtual reality (VR), intelligent driving, and dynamic content delivery, have emerged and been widely used [1], [2], [4], [6]. It is difficult for the traditional cloud data center to meet the performance requirements due to the long distance from massive terminals. Mobile Edge Computing (MEC) is a promising framework to solve this problem by deploying edge servers at base stations to supply computation, storage, and networking resources for multiple users [3]. However, the finite capabilities of edge servers and the erratic activities of multiple end-users pose challenges in guaranteeing the quality of service (QoS). Therefore, there are two key problems: (i) How to guarantee the QoS to avoid service interruption with unknown trajectories when users are away from the original edge servers? (ii) How to realize service provisioning, and updating the services that can efficiently utilize the limited resources without overwhelming the cost constraint? In this paper, we investigate the service provisioning and updating problem under the multiple-users scenario by improving the performance of services with a long-term cost constraint. Fig. 1.

An illustrating example.