虚拟化数据中心中可生存的虚拟基础设施映射

Jielong Xu, Jian Tang, K. Kwiat, Weiyi Zhang, G. Xue
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引用次数: 88

摘要

在虚拟化的数据中心中,通过创建冗余的虚拟机作为虚拟机的备份,可以在虚拟机或服务器出现故障时,将受影响的业务快速切换到备份虚拟机上,从而提高数据中心的生存能力。为了实现灵活高效的资源管理,我们建议使用服务感知方法,将多个相关vm及其备份组合在一起,形成服务或租户的可生存虚拟基础设施(SVI)。这种系统中的一个基本问题是确定如何将每个SVI映射到物理数据中心网络,从而在满足每个VM的资源需求和保证故障前后VM之间的带宽需求的约束下最大限度地降低运营成本。这个问题可以自然地分为两个子问题:虚拟机放置(VMP)和虚拟链路映射(VLM)。我们提出了这个映射问题的一般优化框架。然后给出了求解VMP子问题的有效算法和求解VLM子问题的最优多项式时间算法,可作为框架中的子程序使用。我们还提出了一种有效的启发式算法来联合解决这两个子问题。基于Syracuse University绿色数据中心收集的真实VM数据轨迹的大量仿真结果表明,与First Fit下降(FFD)和基于单最短路径的基线算法相比,我们的VMP+VLM算法和联合算法都显着减少了保留带宽,并且在活动服务器数量方面产生了相当的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Survivable Virtual Infrastructure Mapping in Virtualized Data Centers
In a virtualized data center, survivability can be enhanced by creating redundant Virtual Machines (VMs) as backup for VMs such that after VM or server failures, affected services can be quickly switched over to backup VMs. To enable flexible and efficient resource management, we propose to use a service-aware approach in which multiple correlated VMs and their backups are grouped together to form a Survivable Virtual Infrastructure (SVI) for a service or a tenant. A fundamental problem in such a system is to determine how to map each SVI to a physical data center network such that operational costs are minimized subject to the constraints that each VM's resource requirements are met and bandwidth demands between VMs can be guaranteed before and after failures. This problem can be naturally divided into two sub-problems: VM Placement(VMP) and Virtual Link Mapping (VLM). We present a general optimization framework for this mapping problem. Then we present an efficient algorithm for the VMP sub problem as well as a polynomial-time algorithm that optimally solves the VLM sub problem, which can be used as subroutines in the framework. We also present an effective heuristic algorithm that jointly solves the two sub problems. It has been shown by extensive simulation results based on the real VM data traces collected from the green data center at Syracuse University that compared with the First Fit Descending (FFD) and single shortest path based baseline algorithm, both our VMP+VLM algorithm and joint algorithm significantly reduce the reserved bandwidth, and yield comparable results in terms of the number of active servers.
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