Development of an object-oriented DBMS
OOPLSA '86 Conference proceedings on Object-oriented programming systems, languages and applications
Composite object support in an object-oriented database system
OOPSLA '87 Conference proceedings on Object-oriented programming systems, languages and applications
SIGMOD '89 Proceedings of the 1989 ACM SIGMOD international conference on Management of data
Cactis: a self-adaptive, concurrent implementation of an object-oriented database management system
ACM Transactions on Database Systems (TODS)
Effective clustering of complex objects in object-oriented databases
SIGMOD '91 Proceedings of the 1991 ACM SIGMOD international conference on Management of data
The ObjectStore database system
Communications of the ACM
Self-adaptive, on-line reclustering of complex object data
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
A comparison study of object-oriented database clustering techniques
Information Sciences: an International Journal
AutoAdmin “what-if” index analysis utility
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
OCB: A Generic Benchmark to Evaluate the Performances of Object-Oriented Database Systems
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
Dynamic Clustering in Object Databases Exploiting Effective Use of Relationships Between Objects
ECCOP '96 Proceedings of the 10th European Conference on Object-Oriented Programming
A Clustering Technique for Object Oriented Databases
DEXA '97 Proceedings of the 8th International Conference on Database and Expert Systems Applications
An active system for dynamic vertical partitioning of relational databases
MICAI'11 Proceedings of the 10th international conference on Artificial Intelligence: advances in Soft Computing - Volume Part II
DYMOND: an active system for dynamic vertical partitioning of multimedia databases
Proceedings of the 16th International Database Engineering & Applications Sysmposium
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We present in this paper three dynamic clustering techniques for Object-Oriented Databases (OODBs). The first two, Dynamic, Statistical & Tunable Clustering (DSTC) and StatClust, exploit both comprehensive usage statistics and the inter-object reference graph. They are quite elaborate. However, they are also complex to implement and induce a high overhead. The third clustering technique, called Detection & Reclustering of Objects (DRO), is based on the same principles, but is much simpler to implement. These three clustering algorithm have been implemented in the Texas persistent object store and compared in terms of clustering efficiency (i.e., overall performance increase) and overhead using the Object Clustering Benchmark (OCB). The results obtained showed that DRO induced a lighter overhead while still achieving better overall performance.