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Coordinated Container Migration and Base Station Handover in Mobile Edge Computing
arXiv - CS - Networking and Internet Architecture Pub Date : 2020-09-11 , DOI: arxiv-2009.05682
Mao V. Ngo, Tie Luo, Hieu T. Hoang, and Tony Q.S. Quek

Offloading computationally intensive tasks from mobile users (MUs) to a virtualized environment such as containers on a nearby edge server, can significantly reduce processing time and hence end-to-end (E2E) delay. However, when users are mobile, such containers need to be migrated to other edge servers located closer to the MUs to keep the E2E delay low. Meanwhile, the mobility of MUs necessitates handover among base stations in order to keep the wireless connections between MUs and base stations uninterrupted. In this paper, we address the joint problem of container migration and base-station handover by proposing a coordinated migration-handover mechanism, with the objective of achieving low E2E delay and minimizing service interruption. The mechanism determines the optimal destinations and time for migration and handover in a coordinated manner, along with a delta checkpoint technique that we propose. We implement a testbed edge computing system with our proposed coordinated migration-handover mechanism, and evaluate the performance using real-world applications implemented with Docker container (an industry-standard). The results demonstrate that our mechanism achieves 30%-40% lower service downtime and 13%-22% lower E2E delay as compared to other mechanisms. Our work is instrumental in offering smooth user experience in mobile edge computing.

中文翻译:

移动边缘计算中的协同容器迁移和基站切换

将计算密集型任务从移动用户 (MU) 卸载到虚拟化环境,例如附近边缘服务器上的容器,可以显着减少处理时间,从而减少端到端 (E2E) 延迟。但是,当用户移动时,此类容器需要迁移到更靠近 MU 的其他边缘服务器,以保持较低的 E2E 延迟。同时,MU 的移动性需要在基站之间进行切换,以保持 MU 和基站之间的无线连接不中断。在本文中,我们通过提出一种协调的迁移-切换机制来解决容器迁移和基站切换的联合问题,以实现低端到端延迟和最小化服务中断的目标。该机制以协调的方式确定迁移和切换的最佳目的地和时间,以及我们提出的增量检查点技术。我们使用我们提出的协调迁移-切换机制实现了一个测试平台边缘计算系统,并使用使用 Docker 容器(行业标准)实现的实际应用程序评估性能。结果表明,与其他机制相比,我们的机制减少了 30%-40% 的服务停机时间和 13%-22% 的端到端延迟。我们的工作有助于在移动边缘计算中提供流畅的用户体验。并使用使用 Docker 容器(行业标准)实现的实际应用程序评估性能。结果表明,与其他机制相比,我们的机制减少了 30%-40% 的服务停机时间和 13%-22% 的端到端延迟。我们的工作有助于在移动边缘计算中提供流畅的用户体验。并使用使用 Docker 容器(行业标准)实现的实际应用程序评估性能。结果表明,与其他机制相比,我们的机制减少了 30%-40% 的服务停机时间和 13%-22% 的端到端延迟。我们的工作有助于在移动边缘计算中提供流畅的用户体验。
更新日期:2020-09-15
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