Large-Scale VM Placement with Disk Anti-Colocation Constraints Using Hierarchical Decomposition and Mixed Integer Programming

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.