UMS: Live Migration of Containerized Services across Autonomous Computing Systems
UMS: Live Migration of Containerized Services across Autonomous Computing Systems
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DOI：
10.1109/globecom54140.2023.10437519
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发表时间：
2023-09
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影响因子：
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通讯作者：
Thanawat Chanikaphon;Mohsen Amini Salehi
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作者：
Thanawat Chanikaphon;Mohsen Amini Salehi
部署在各种计算系统中的容器化服务，例如Edge和Cloud，希望实时迁移支持以实现用户移动性，弹性和负载平衡。为了实现这种无处不在，有效的服务迁移，实时迁移解决方案需要处理用户对基础计算系统具有各种权威级别（完全控制，有限控制或没有控制的情况）。在这些层面上支持实时迁移是互操作性的基石，并且可以在各种形式的分布式系统中解锁几种用例。因此，在这项研究中，我们开发了一种普遍存在的迁移解决方案（称为UMS），对于给定的容器化服务，可以自动识别可行的迁移方法，然后在自主计算系统上无缝执行迁移。 UMS不会干扰编目手柄的方式，并且可以在没有编排者参与的情况下协调迁移。此外，ums是管弦乐器 - 静态的，即可以将其插入任何基础的编排平台中。 UMS配备了可以在编排，容器和服务水平协调和执行实时迁移的新颖方法。实验结果表明，对于单进程容器，服务级别的方法以及对于具有小$ $（<128 \ MathBf {MiB}）的多进程容器和服务停机时间。为了证明UMS在实现互操作性和多云场景方面的潜力，我们检查了它以在跨异构编排者以及Microsoft Azure和Google Cloud之间进行实时服务迁移。
Containerized services deployed within various computing systems, such as edge and cloud, desire live migration support to enable user mobility, elasticity, and load balancing. To enable such a ubiquitous and efficient service migration, a live migration solution needs to handle circumstances where users have various authority levels (full control, limited control, or no control) over the underlying computing systems. Supporting the live migration at these levels serves as the cornerstone of interoperability, and can unlock several use cases across various forms of distributed systems. As such, in this study, we develop a ubiquitous migration solution (called UMS) that, for a given containerized service, can automatically identify the feasible migration approach, and then seamlessly perform the migration across autonomous computing systems. UMS does not interfere with the way the orchestrator handles containers and can coordinate the migration without the orchestrator involvement. Moreover, UMS is orchestrator-agnostic, i.e., it can be plugged into any underlying orchestrator platform. UMS is equipped with novel methods that can coordinate and perform the live migration at the orchestrator, container, and service levels. Experimental results show that for single-process containers, the service-level approach, and for multi-process containers with small $(< 128 \mathbf{MiB})$ memory footprint, the container-level migration approach lead to the lowest migration overhead and service downtime. To demonstrate the potential of UMS in realizing interoperability and multi-cloud scenarios, we examined it to perform live service migration across heterogeneous orchestrators, and between Microsoft Azure and Google Cloud.