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STEP: Self-Tuning Energy-safe Predictors

DocUID: 2005-004 Full Text: PDF

Author: James Larkby-Lahet, Ganesh Santhanakrishnan, Ahmed Amer, Panos K. Chrysanthis

Abstract: Data access prediction has been proposed as a mechanism to overcome latency lag, and more recently as a means of conserving energy in mobile systems. We present a fully adaptive predictor, that can optimize itself for any arbitrary workload, while simultaneously offering simple adjustment of goals between energy conservation and latency reduction. Our algorithm, STEP, achieves power savings on mobile computers by eliminating more data fetches, which would otherwise have caused excess energy to be consumed in accessing local storage devices or using the wireless interface to fetch remote data. We have demonstrated our algorithm to perform as well as some of the best access predictors, while incurring almost none of the associated increase in I/O workloads typical of their use. Our algorithm reduced average response times by approximately 50% compared to an LRU cache, while requiring less than half the I/O operations that traditional predictors would require to achieve the same performance, thereby incurring no energy penalty.

Published In: Proc. of the 5th International Conference in Mobile Data Management

ISBN: 1-59593-041-8

Pages: pp. 125-133

Place Published: Ayia Napa, Cyprus

Year Published: 2005

Note: DOI:10.1145/1071246.1071264

Project: Others Subject Area: Mobile Databases, Caching

Publication Type: Conference Paper

Sponsor: Pitt Start-up 2002, NSF ITR ANI-0325353

Citation:Text Latex BibTex XML James Larkby-Lahet, Ganesh Santhanakrishnan, Ahmed Amer, and Panos K. Chrysanthis. STEP: Self-Tuning Energy-safe Predictors, Proc. of the 5th International Conference in Mobile Data Management (MDM'05), pp. 125-133, 1-59593-041-8, Ayia Napa, Cyprus, May 2005.(DOI:10.1145/1071246.1071264)