ICICA'12 Proceedings of the Third international conference on Information Computing and Applications
Financial Option Market Model for Federated Cloud Environments
UCC '12 Proceedings of the 2012 IEEE/ACM Fifth International Conference on Utility and Cloud Computing
Introducing service-level awareness in the cloud
Proceedings of the 4th annual Symposium on Cloud Computing
Energy and carbon-efficient placement of virtual machines in distributed cloud data centers
Euro-Par'13 Proceedings of the 19th international conference on Parallel Processing
Proceedings of the 5th ACM/SPEC international conference on Performance engineering
A Traffic-Aware Virtual Machine Placement Method for Cloud Data Centers
UCC '13 Proceedings of the 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing
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Much recent research has been devoted to investigating algorithms for allocating virtual machines (VMs) to physical machines (PMs) in infrastructure clouds. Many such algorithms address distinct problems, such as initial placement, consolidation, or tradeoffs between honoring service-level agreements and constraining provider operating costs. Even where similar problems are addressed, each individual research team evaluates proposed algorithms under distinct conditions, using various techniques, often targeted to a small collection of VMs and PMs. In this paper, we describe an objective method that can be used to compare VM-placement algorithms in large clouds, covering tens of thousands of PMs and hundreds of thousands of VMs. We demonstrate our method by comparing 18 algorithms for initial VM placement in on-demand infrastructure clouds. We compare algorithms inspired by open-source code for infrastructure clouds, and by the online bin-packing literature.