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A Fine-Grained Model for Adaptive On-Demand Provisioning of CPU Shares in Data Centers

  • Emerson Loureiro
  • Paddy Nixon
  • Simon Dobson
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5343)

Abstract

Data Centers usually host different third party applications, each of them possibly having different requirements in terms of QoS. To achieve them, sufficient resources, like CPU and memory, must be allocated to each application. However, workload fluctuations might arise, and so, resource demands will vary. Allocations based on worst/average case scenarios can lead to non-desirable results. A better approach is then to assign resources on demand. Also, due to the complexity and size of current and future systems, self-adaptive solutions are essential. In this paper, we then present Grains, a self-adaptive approach for resource management in Data Centers under varying workload.

Keywords

IEEE Computer Society Physical Machine Application Class Local Share Global Controller 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Emerson Loureiro
    • 1
  • Paddy Nixon
    • 1
  • Simon Dobson
    • 1
  1. 1.Systems Research Group School of Computer Science and InformaticsUniversity College DublinDublinIreland

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