Vertical partitioning algorithms for database design
ACM Transactions on Database Systems (TODS)
Data allocation in distributed database systems
ACM Transactions on Database Systems (TODS)
Agglomerative clustering of a search engine query log
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
How to solve it: modern heuristics
How to solve it: modern heuristics
The effects of parallel processing on update response time in distributed database design
ICIS '00 Proceedings of the twenty first international conference on Information systems
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
On Clustering Validation Techniques
Journal of Intelligent Information Systems
Automatic Generation of Control Parameters for the Threshold Accepting Algorithm
MICAI '02 Proceedings of the Second Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
A Distribution Design Methodology for Object DBMS
Distributed and Parallel Databases
Distribution Design of Logical Database Schemas
IEEE Transactions on Software Engineering
DB2 design advisor: integrated automatic physical database design
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
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In this paper we approach the solution of large instances of the distribution design problem. Traditional approaches do not consider that the size of the instances can significantly affect the efficiency of the solution process. This paper shows the feasibility to solve large scale instances of the distribution design problem by compressing the instance to be solved. The goal of the compression is to obtain a reduction in the amount of resources needed to solve the original instance, without significantly reducing the quality of its solution. In order to preserve the solution quality, the compression summarizes the access pattern of the original instance using clustering techniques. In order to validate the approach we tested it on a new model of the replicated version of the distribution design problem that incorporates generalized database objects. The experimental results show that our approach permits to reduce the computational resources needed for solving large instances, using an efficient clustering algorithm. We present experimental evidence of the clustering efficiency of the algorithm.