DMCA
Optimal Prefetching via Data Compression (1995)
Cached
Download Links
| Citations: | 258 - 7 self |
BibTeX
@MISC{Vitter95optimalprefetching,
author = {Jeffrey Scott Vitter and P. Krishnan},
title = {Optimal Prefetching via Data Compression},
year = {1995}
}
Share
 |
 |
 |
 |
||
OpenURL
Abstract
Caching and prefetching are important mechanisms for speeding up access time to data on secondary storage. Recent work in competitive online algorithms has uncovered several promising new algorithms for caching. In this paper we apply a form of the competitive philosophy for the first time to the problem of prefetching to develop an optimal universal prefetcher in terms of fault ratio, with particular applications to large-scale databases and hypertext systems. Our prediction algorithms for prefetching are novel in that they are based on data compression techniques that are both theoretically optimal and good in practice. Intuitively, in order to compress data effectively, you have to be able to predict future data well, and thus good data compressors should be able to predict well for purposes of prefetching. We show for powerful models such as Markov sources and nth order Markov sources that the page fault rates incurred by our prefetching algorithms are optimal in the limit for almost all sequences of page requests.
Keyphrases
data compression optimal prefetching good data compressor page fault rate important mechanism recent work secondary storage prefetching algorithm page request future data large-scale database hypertext system markov source competitive philosophy fault ratio access time prediction algorithm powerful model data compression technique nth order markov source optimal universal prefetcher new algorithm particular application first time competitive online algorithm
