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A Dynamic Markov Biclustering Cache Replacement Policy for Mobile Environment

Published on None 2011 by Hariram Chavan, Suneeta Sane, H. B. Kekre
International Conference on Technology Systems and Management
Foundation of Computer Science USA
ICTSM - Number 1
None 2011
Authors: Hariram Chavan, Suneeta Sane, H. B. Kekre
da7273fd-c755-4492-8607-64b7068d3366

Hariram Chavan, Suneeta Sane, H. B. Kekre . A Dynamic Markov Biclustering Cache Replacement Policy for Mobile Environment. International Conference on Technology Systems and Management. ICTSM, 1 (None 2011), 11-17.

@article{
author = { Hariram Chavan, Suneeta Sane, H. B. Kekre },
title = { A Dynamic Markov Biclustering Cache Replacement Policy for Mobile Environment },
journal = { International Conference on Technology Systems and Management },
issue_date = { None 2011 },
volume = { ICTSM },
number = { 1 },
month = { None },
year = { 2011 },
issn = 0975-8887,
pages = { 11-17 },
numpages = 7,
url = { /proceedings/ictsm/number1/2777-13/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Technology Systems and Management
%A Hariram Chavan
%A Suneeta Sane
%A H. B. Kekre
%T A Dynamic Markov Biclustering Cache Replacement Policy for Mobile Environment
%J International Conference on Technology Systems and Management
%@ 0975-8887
%V ICTSM
%N 1
%P 11-17
%D 2011
%I International Journal of Computer Applications
Abstract

In mobile database systems caching proved itself as an important technique to optimize the way a mobile database is used. The desired caching can be achieved by convincingly accurate prediction of data items for the present and future query processing. Prefetching is a commonly used strategy to cut down network resources consumed as well as the access latencies observed by end users. In this paper, we propose a Dynamic Markov Biclustering Cache Replacement Policy (DMBCRP) which is a sophisticated combination of caching and prefetching for mobile database environment. We dynamically bicluster the data for location based services with second and/or first order Markov Model to predict the new data item(s) to be fetched based on user access patterns. The java implementation of DMBCRP, using trip data set and dynamic location specific resource biclustering results in different user access patterns and also user movement patterns.

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Index Terms

Computer Science
Information Sciences

Keywords

Markov model Biclustering caching prefetching users access patterns