NDLI: Markov Model Based Disk Power Management for Data Intensive Workloads

Content Provider	IEEE Xplore Digital Library
Author	Garg, R. Seung Woo Son Kandemir, M. Raghavan, P. Prabhakar, R.
Copyright Year	2009
Abstract	In order to meet the increasing demands of present and upcoming data-intensive computer applications, there has been a major shift in the disk subsystem, which now consists of more disks with higher storage capacities and higher rotational speeds. These have made the disk subsystem a major consumer of power, making disk power management an important issue. People have considered the option of spinning down the disk during periods of idleness or serving the requests at lower rotational speeds when performance is not an issue. Accurately predicting future disk idle periods is crucial to such schemes. This paper presents a novel disk-idleness prediction mechanism based on Markov models and explains how this mechanism can be used in conjunction with a three-speed disk. Our experimental evaluation using a diverse set of workloads indicates that (i) prediction accuracies achieved by the proposed scheme are very good (87.5% on average); (ii) it generates significant energy savings over the traditional power-saving method of spinning down the disk when idle (35.5% onaverage); (iii) it performs better than a previously proposed multi-speed disk management scheme (19% on average); and (iv) the performance penalty is negligible (less than 1% on average). Overall, our implementation and experimental evaluation using both synthetic disk traces and traces extracted from real applications demonstrate the feasibility of a Markov-model-based approach to saving disk power.
Starting Page	76
Ending Page	83
File Size	394144
Page Count	8
File Format	PDF
ISBN	9781424439355
DOI	10.1109/CCGRID.2009.67
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-05-18
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Energy management Power system modeling Predictive models Energy consumption Spinning Costs Batteries Grid computing Mathematical model Mathematics prediction Markov mulit-speed power
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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