在多个公有云之间实现虚拟机同构和自动化迁移

Marc Xavier, I. S. Sette, C. Ferraz
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引用次数: 0

摘要

这项工作的目的是通过使用公共云(如亚马逊网络服务(AWS)、微软Azure (AZ)和谷歌云平台(GCP))的场景,分析使用称为Kumo的拟议解决方案自动迁移虚拟机(vm)所需的步骤。考虑同构云和异构云之间的总迁移时间(TTM)度量,进行了性能评估。在同质场景中,即源云和目标云来自同一提供商,但位于不同的数据中心的场景,在Azure云之间的迁移效果最好,平均TTM为45m59秒。对于异构,最佳场景是GCP-AWS迁移,TTM为45m56秒。对虚拟机自动化迁移的9个步骤进行了分析,发现其中5个步骤对测试的9个场景的TTM有显著影响,在94.01%到99.44%之间。
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Homogeneous and Automated Migration of Virtual Machines Between Multiple Public Clouds
The objective of this work is to analyze the required steps for automated migration of Virtual Machines (VMs) using a proposed solution, called Kumo, through scenarios using public clouds, such as Amazon Web Services (AWS), Microsoft Azure (AZ) and Google Cloud Platform (GCP). A performance evaluation is carried out considering the Total Migration Time (TTM) metric between homogeneous and heterogeneous clouds. Among the homogeneous scenarios, which are those in which the source and destination clouds are from the same provider, but in different data centers, the best result occurred in migrations between Azure clouds, with average TTM of 45m59s. For heterogeneous, the best scenario was the GCP-AWS migration, with TTM of 45m56s. The nine steps for the automated migration of VMs were analyzed, showing that five of them combined significantly impacted, between 94.01% and 99.44%, the TTM of the 9 scenarios tested.
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