FT-VMP: Fault-Tolerant Virtual Machine Placement in Cloud Data Centers

Christopher Gonzalez, Bin Tang
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引用次数: 6

Abstract

Virtual machine (VM) replication is an effective technique in cloud data centers to achieve fault-tolerance, load-balance, and quick-responsiveness to user requests. In this paper we study a new fault-tolerant VM placement problem referred to as FT-VMP. Given that different VM has different fault-tolerance requirement (i.e., difference VM requires different number of replica copies) and compatibility requirement (i.e., some VMs and their replicas cannot be placed into some physical machines (PMs) due to software or platform incompatibility), FT-VMP studies how to place VM replica copies inside cloud data centers in order to minimize the number of PMs storing VM replicas, under the constraints that i) for fault-tolerant purpose, replica copies of the same VM cannot be placed inside the same PM and ii) each PM has a limited amount of storage capacity. We first prove that FT-VMP is NP-hard. We then design an integer linear programming (ILP)-based algorithm to solve it optimally. As ILP takes time to compute thus is not suitable for large scale cloud data centers, we design a suite of efficient and scalable heuristic fault-tolerant VM placement algorithms. We show that a) ILP-based algorithm outperforms the state-of-the-art VM replica placement in a wide range of network dynamics and b) that all our fault-tolerant VM placement algorithms are able to turn off significant number of PMs to save energy in cloud data centers. In particular, we show that our algorithms can consolidate (i.e., turn off) around 100 PMs in a small data center of 256 PMs and 700 PMs in a large data center of 1028PMs.
FT-VMP:云数据中心中的容错虚拟机布局
虚拟机(VM)复制是云数据中心实现容错、负载均衡和快速响应用户请求的有效技术。本文研究了一种新的容错虚拟机放置问题,称为FT-VMP。考虑到不同的VM具有不同的容错需求(即不同的VM需要不同数量的副本)和兼容性需求(即某些VM及其副本由于软件或平台不兼容而无法放置到某些物理机(pm)中),FT-VMP研究如何将VM副本放置在云数据中心内,以尽量减少存储VM副本的pm的数量,在以下约束条件下:i)用于容错目的;同一虚拟机的副本不能放置在同一个PM内;ii)每个PM的存储容量有限。我们首先证明了FT-VMP是np困难的。然后,我们设计了一个基于整数线性规划(ILP)的算法来最优求解该问题。由于ILP需要时间来计算,因此不适合大规模云数据中心,我们设计了一套高效且可扩展的启发式容错VM放置算法。我们表明,a)基于ilp的算法在广泛的网络动态中优于最先进的虚拟机副本放置,b)我们所有的容错虚拟机放置算法都能够关闭大量的pm,以节省云数据中心的能源。特别是,我们展示了我们的算法可以在256个pm的小型数据中心中合并(即关闭)大约100个pm,在1028个pm的大型数据中心中合并700个pm。
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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