Planning vs. Dynamic Control: Resource Allocation in Corporate Clouds

Andreas Wolke, Martin Bichler, Thomas Setzer

Research output: Contribution to journalArticlepeer-review

34 Scopus citations


Nowadays corporate data centers leverage virtualization technology to cut operational and management costs. Virtualization allows splitting and assigning physical servers to virtual machines (VM) that run particular business applications. This has led to a new stream in the capacity planning literature dealing with the problem of assigning VMs with volatile demands to physical servers in a static way such that energy costs are minimized. Live migration technology allows for dynamic resource allocation, where a controller responds to overload or underload on a server during runtime and reallocates VMs in order to maximize energy efficiency. Dynamic resource allocation is often seen as the most efficient means to allocate hardware resources in a data center. Unfortunately, there is hardly any experimental evidence for this claim. In this paper, we provide the results of an extensive experimental analysis of both capacity management approaches on a data center infrastructure. We show that with typical workloads of transactional business applications dynamic resource allocation does not increase energy efficiency over the static allocation of VMs to servers and can even come at a cost, because migrations lead to overheads and service disruptions.

Original languageEnglish
Article number6910277
Pages (from-to)322-335
Number of pages14
JournalIEEE Transactions on Cloud Computing
Issue number3
StatePublished - 1 Jul 2016


  • Capacity planning
  • IT service management
  • resource allocation


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