Server frequency control using markov decision processes

Lydia Y. Chen, Natarajan Gautam

Research output: Chapter in Book/Entry/PoemConference contribution

7 Scopus citations


For a wide range of devices and servers, Dynamic Frequency Scaling (DFS) can reduce energy consumption to various degrees by appropriately trading-off system performance. Efficient DFS policies are able to adjust server frequencies by extrapolating the transition of the highly varying workload without incurring much of implementation overhead. This paper models DFS policies of a single server using Markov Decision Processes (MDP). To accommodate the highly varying nature of workload in the proposed MDP, we adopt fluid approximation based on continuous time Markov chain and discrete time Markov chain modeling for the fluid workload generator respectively. Accordingly, we design two frequency controllers (FC), namely C-FC and D-FC, corresponding to the continuous and discrete modeling of the workload generator. We evaluate the proposed policies on synthetic and web traces. The proposed C-FC and D-FC schemes ensure performance satisfaction with moderate energy saving as well as ease of implementation, in comparison with existing DFS policies.

Original languageEnglish (US)
Title of host publicationIEEE INFOCOM 2009 - The 28th Conference on Computer Communications
Number of pages5
StatePublished - 2009
Externally publishedYes
Event28th Conference on Computer Communications, IEEE INFOCOM 2009 - Rio de Janeiro, Brazil
Duration: Apr 19 2009Apr 25 2009

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X


Conference28th Conference on Computer Communications, IEEE INFOCOM 2009
CityRio de Janeiro

ASJC Scopus subject areas

  • General Computer Science
  • Electrical and Electronic Engineering


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