Online Live VM Migration Algorithms to Minimize Total Migration Time and Downtime

Nikos Tziritas, Thanasis Loukopoulos, S. Khan, Chengzhong Xu, Albert Y. Zomaya
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引用次数: 6

Abstract

Virtual machine (VM) migration is a widely used technique in cloud computing systems to increase reliability. There are also many other reasons that a VM is migrated during its lifetime, such as reducing energy consumption, improving performance, maintenance, etc. During a live VM migration, the underlying VM continues being up until all or part of its data has been transmitted from source to destination. The remaining data are transmitted in an off-line manner by suspending the corresponding VM. The longer the off-line transmission time, the worse the performance of the respective VM. The above is because during the off-line data transmission, the VM service is down. Because a running VM's memory is subject to changes, already transmitted data pages may get dirtied and thus needing re-transmission. The decision of when suspending the VM is not a trivial task at all. The above is justified by the fact that when suspending the VM early we may result in transmitting off-line a significant amount of data degrading thus the VM's performance. On the other hand, a long waiting time to suspend the VM may result in re-transmitting a huge amount of dirty data, leading in that way to waste of resources. In this paper, we tackle the joint problem of minimizing both the total VM migration time (reflecting the resources spent during a migration) and the VM downtime (reflecting the performance degradation). The aforementioned objective functions are weighted according to the needs of the underlying cloud provider/user. To tackle the problem, we propose an online deterministic algorithm resulting in an strong competitive ratio, as well as a randomized online algorithm achieving significantly better results against the deterministic algorithm.
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在线虚拟机迁移算法,最大限度地减少总迁移时间和停机时间
虚拟机(VM)迁移是云计算系统中广泛使用的一种提高可靠性的技术。虚拟机在其生命周期内迁移还有许多其他原因,如降低能耗、提高性能、维护等。在虚拟机迁移过程中,底层虚拟机一直处于运行状态,直到其全部或部分数据从源传输到目标为止。剩余数据通过挂起对应的虚拟机离线传输。离线传输时间越长,对应虚拟机的性能越差。这是因为在离线传输数据时,虚拟机服务关闭。由于正在运行的虚拟机的内存可能会发生变化,已经传输的数据页可能会被弄脏,因此需要重新传输。决定何时挂起虚拟机根本不是一项简单的任务。上述理由是合理的,因为当早期挂起VM时,我们可能会导致离线传输大量数据,从而降低VM的性能。另一方面,等待挂起虚拟机的时间过长,可能导致大量脏数据重传,造成资源浪费。在本文中,我们解决了最小化总VM迁移时间(反映迁移期间花费的资源)和VM停机时间(反映性能下降)的联合问题。根据底层云提供商/用户的需求对上述目标函数进行加权。为了解决这个问题,我们提出了一种在线确定性算法,该算法具有很强的竞争比,以及一种随机在线算法,其结果明显优于确定性算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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