Hierarchical Clustering in Object Oriented Data Models with Complex Class Relationships

Class fragmentation is an essential phase in the design of Distributed Object Oriented Databases (DOODB). Horizontal and vertical fragmentation are the two commonly used fragmentation techniques. We propose here two new methods for horizontal fragmentation of objects with complex attributes. They rely on AI clustering techniques for grouping objects into fragments. Both methods take into account the inheritance and aggregation/association hierarchies. We provide quality and performance evaluations using a partition evaluator function.