Title
Distribution design in distributed databases using clustering to solve large instances
Abstract
In this paper we approach the solution of large instances of the distribution design problem. The traditional approaches do not consider that the size of the instances can significantly reduce the efficiency of the solution process, which only involves a model of the problem and a solution algorithm. We propose a new approach that incorporates multiple models and algorithms and mechanisms for instance compression, for increasing the scalability of the solution process. In order to validate the approach we tested it on a new model of the replicated version of the distribution design problem which incorporates generalized database objects, and a method for instance compression that uses clustering techniques. The experimental results, utilizing typical Internet usage loads, show that our approach permits to reduce at least 65% the computational resources needed for solving large instances, without significantly reducing the quality of its solution.
Year
DOI
Venue
2005
10.1007/11576235_69
ISPA
Keywords
Field
DocType
distributed database
Data mining,Computer science,Distributed database,Cluster analysis,Access frequency,Object oriented databases,Scalability,Distributed computing,The Internet,Multiple Models
Conference
Volume
ISSN
ISBN
3758
0302-9743
3-540-29769-3
Citations 
PageRank 
References 
0
0.34
8
Authors
6
Name
Order
Citations
PageRank
Joaquín Perez-Ortega131.75
R. Rodolfo Pazos2246.92
Jose Florez300.34
J. Barbosa400.34
E. Diaz500.34
J. Villanueva600.34