Dynamic Load Balancing for Parallel Association Rule Mining on Heterogenous PC Cluster Systems.
Masahisa Tamura, Masaru Kitsuregawa:
Dynamic Load Balancing for Parallel Association Rule Mining on Heterogenous PC Cluster Systems.
VLDB 1999: 162-173@inproceedings{DBLP:conf/vldb/TamuraK99,
author = {Masahisa Tamura and
Masaru Kitsuregawa},
editor = {Malcolm P. Atkinson and
Maria E. Orlowska and
Patrick Valduriez and
Stanley B. Zdonik and
Michael L. Brodie},
title = {Dynamic Load Balancing for Parallel Association Rule Mining on
Heterogenous PC Cluster Systems},
booktitle = {VLDB'99, Proceedings of 25th International Conference on Very
Large Data Bases, September 7-10, 1999, Edinburgh, Scotland,
UK},
publisher = {Morgan Kaufmann},
year = {1999},
isbn = {1-55860-615-7},
pages = {162-173},
ee = {db/conf/vldb/TamuraK99.html},
crossref = {DBLP:conf/vldb/99},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX
Abstract
The dynamic load balancing strategies for parallel
association rule mining are proposed under
heterogeneous PC cluster environment.
PC cluster is recently regarded as one of the
most promising platforms for heavy data intensive
applications, such as decision support
query processing and data mining. The development
period of PC hardware is becoming extremely short,
which results in heterogeneous system, where the
clock cycle of CPU, the performance/capacity of disk
drives, etc are different among component PC's.
Heterogeneity is inevitable. Basically, current algorithms
assume the homogeneity. Thus if we naively apply them to
heterogeneous system, its performance is far below
expectation. We need some new methodologies to handle
heterogeneity. In this paper, we propose the new dynamic
load balancing methods for association rule mining,
which works under heterogeneous system. Two strategies,
called candidate migration and transaction migration are
proposed. Initially first one is invoked. When the load
imbalance cannot be resolved with the first method, the
second one is employed, which is costly but more effective
for strong imbalance. We have implemented them on the PC
cluster system with two different types of PCs: one with
Pentium Pro, the other one with Pentium II. The experimental
results confirm that the proposed approach can very effectively
balance the workload among heterogeneous PCs.
Copyright © 1999 by the VLDB Endowment.
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Online Paper
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BibTeX
Printed Edition
Malcolm P. Atkinson, Maria E. Orlowska, Patrick Valduriez, Stanley B. Zdonik, Michael L. Brodie (Eds.):
VLDB'99, Proceedings of 25th International Conference on Very Large Data Bases, September 7-10, 1999, Edinburgh, Scotland, UK.
Morgan Kaufmann 1999, ISBN 1-55860-615-7
Contents BibTeX
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BibTeX
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