Predictive Dynamic Load Balancing of Parallel and Distributed Rule and Query Processing.
Hasanat M. Dewan, Salvatore J. Stolfo, Mauricio A. Hernández, Jae-Jun Hwang:
Predictive Dynamic Load Balancing of Parallel and Distributed Rule and Query Processing.
SIGMOD Conference 1994: 277-288@inproceedings{DBLP:conf/sigmod/DewanSHH94,
author = {Hasanat M. Dewan and
Salvatore J. Stolfo and
Mauricio A. Hern{\'a}ndez and
Jae-Jun Hwang},
editor = {Richard T. Snodgrass and
Marianne Winslett},
title = {Predictive Dynamic Load Balancing of Parallel and Distributed
Rule and Query Processing},
booktitle = {Proceedings of the 1994 ACM SIGMOD International Conference on
Management of Data, Minneapolis, Minnesota, May 24-27, 1994},
publisher = {ACM Press},
year = {1994},
pages = {277-288},
ee = {http://doi.acm.org/10.1145/191839.191893, db/conf/sigmod/DewanSHH94.html},
crossref = {DBLP:conf/sigmod/94},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
Abstract
Expert Databases are environments that support the
processing of rule programs against a disk resident database.
They occupy a position intermediate between active and deductive databases,
with respect to the level of abstraction of the underlying rule language.
The operational semantics of the rule language influences the
problem solving strategy, while the architecture of
the processing environment determines efficiency and scalability.
In this paper, we present elements of the PARADISER architecture and
its kernel rule language, PARULEL.
The PARADISER environment provides support for parallel and distributed
evaluation of rule programs, as well as static and dynamic load
balancing protocols that predictively balance a computation at runtime.
This combination of features results in a scalable database rule and
complex query processing architecture. We validate our claims by analyzing the
performance of the system for two realistic test cases. In particular,
we show how the performance of a parallel implementation of
transitive closure is significantly
improved by predictive dynamic load balancing.
Copyright © 1994 by the ACM,
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Printed Edition
Richard T. Snodgrass, Marianne Winslett (Eds.):
Proceedings of the 1994 ACM SIGMOD International Conference on Management of Data, Minneapolis, Minnesota, May 24-27, 1994.
ACM Press 1994
,
SIGMOD Record 23(2),
June 1994
Contents
[Abstract and Index Terms]
[Full Text in PDF Format, 1334 KB]
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Referenced by
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Morgan Kaufmann 1996, ISBN 1-55860-304-2
Contents
Copyright © Mon Nov 2 21:12:01 2009
by Michael Ley (ley@uni-trier.de)