Optimal Container Migration for Mobile Edge Computing: Algorithm, System Design and Implementation

IEEE Access

卷:9

Wooyeol Choi¹  Jenn-Wei Lin²  Motassem Al-Tarazi³  Taewoon Kim⁴ 

[1]Department of Computer Engineering, Chosun University, Gwangju, Republic of Korea

[2]|Department of Computer Science and Information Engineering, Fu Jen Catholic University, New Taipei City, Taiwan

[3]|School of Computing, University of Nebraska-Lincoln, Lincoln, NE, USA

[4]|School of Software, Hallym University, Chuncheon-si, Republic of Korea

关键词: Container;    docker;    edge computing;    implementation;    live migration;    optimal decision;   

DOI  :  10.1109/ACCESS.2021.3131643

来源: DOAJ

【 摘 要 】

Edge computing is a promising alternative to cloud computing for offloading computationally heavy tasks from resource-constrained mobile user devices. Placed at the edge of the network, edge computing is particularly advantageous to delay-limited applications for having a short distance to end-users. However, when a mobile user moves away from the service coverage of the associated edge server, the advantage gradually vanishes, increasing response time. Although service migration has been studied to address this problem focusing on minimizing the service downtime, both zero-downtime and the amount of traffic generated as a result of migration need further study. In this paper, an optimal live migration for containerized edge computing service is studied. This paper presents three zero-downtime migration techniques based on state duplication and state reproduction techniques, and then, proposes an optimal migration technique selection algorithm that jointly minimizes the response time and network traffic during migration. For validation and performance comparison, the proposed migration techniques are implemented on off-the-shelf hardware with Linux operating system. The evaluation results showed that compared with a naive migration, the optimal approach reduced the response time and network load by at least 74.75% and 94.79%, respectively, under considered scenarios.

【 授权许可】

Unknown