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首页> 外文期刊>IEEE Transactions on Parallel and Distributed Systems >Large-Scale VM Placement with Disk Anti-Colocation Constraints Using Hierarchical Decomposition and Mixed Integer Programming
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Large-Scale VM Placement with Disk Anti-Colocation Constraints Using Hierarchical Decomposition and Mixed Integer Programming

机译：使用分层分解和混合整数编程的磁盘反并置约束的大型VM放置

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摘要

As computational clouds offer increasingly sophisticated services, there is a dramatic increase in the variety and complexity of virtual machine (VM) placement problems. In this paper, we consider a VM placement problem with a special type of anti-colocation requirements—disk anti-colocation—which stipulate that, for every VM assigned to a PM (physical machine), its virtual disks should be spread out across the physical disks of the PM. Once such a requirement is met, the users of the VM can expect improved disk I/O performance. There will also be improvement in fault tolerance and availability. For scalable solutions, we propose a method that combines hierarchical decomposition with mixed integer programming (MIP), where the basic building blocks are independent, small MIP subproblems. We provide experimental results to demonstrate the effectiveness of the proposed method. We show that it is scalable and achieves high performance with respect to the optimization objective.
机译：随着计算云提供越来越复杂的服务，虚拟机（VM）放置问题的种类和复杂性急剧增加。在本文中，我们考虑具有特殊类型的反定位要求（磁盘反定位）的VM放置问题，该问题规定，对于分配给PM（物理机）的每个VM，其虚拟磁盘应分布在整个虚拟机上。 PM的物理磁盘。一旦满足了这样的要求，VM的用户就可以期望提高磁盘I / O性能。容错能力和可用性也将得到改善。对于可伸缩解决方案，我们提出了一种将层次分解与混合整数编程（MIP）相结合的方法，其中基本构件是独立的小MIP子问题。我们提供实验结果来证明所提出方法的有效性。我们证明它具有可扩展性，并在优化目标方面实现了高性能。

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