FAST: Flexible and Low-Latency State Transfer in Mobile Edge Computing

Tung V Doan,Frank H P Fitzek,Giang T Nguyen,Martin Reisslein

doi:10.1109/access.2021.3105583

Abstract

Mobile Edge Computing (MEC) brings the benefits of cloud computing, such as computation, networking, and storage resources, close to end users, thus reducing end-to-end latency and enabling various novel use cases, such as vehicle platooning, autonomous driving, and the tactile internet. However, frequent user mobility makes it challenging for the MEC to guarantee the close proximity to the users. To tackle this challenge, the underlying network has to be capable of seamlessly migrating applications between multiple MEC sites. This application migration requires the quick and flexible migration of the application states without service interruption, while minimizing the state transfer cost. In this article, we first study the state transfer optimization problem in the MEC. To solve this problem, we propose a metaheuristic algorithm based on Tabu search. We then propose Flexible and Low-Latency State Transfer in Mobile Edge Computing (FAST), the first programmable state forwarding framework. FAST flexibly and directly forwards states between source instance and destination instance based on Software-Defined Networking (SDN). Both simulation results and practical testbed results demonstrate the favorable performance of the proposed Tabu search algorithm and the FAST framework compared to the state-of-the-art schemes.

Highlights

Mobile Edge Computing (MEC) brings the flexibility and elasticity of cloud computing to run the applications in a close proximity of the end users, e.g., at a base station [2]–[8]
The simulation results indicate that our proposed Tabu algorithm significantly outperforms elementary heuristic algorithms and performs close to the optimum, while incurring much lower computational complexity compared to the optimal solution
We have proposed a meta-heuristic algorithm based on Tabu search to solve the MEC state transfer optimization problem

Summary

Introduction

Mobile Edge Computing (MEC) brings the flexibility and elasticity of cloud computing to run the applications in a close proximity of the end users, e.g., at a base station [2]–[8]. A key challenge for the MEC is to continuously maintain running applications in close proximity of the end users according to their movements across the coverage areas of different base stations. I.e., the process of transferring an application from one place to another, requires a consistent operational state before and after the. The downtime is caused by the process of saving, transferring, and recovering the application’s data during the service migration. This consistency requirement should allow an application at a destination instance to resume at the exact running state that it had at the source instance

Objectives

Results

Conclusion