AI clustering techniques: a new approach in horizontal fragmentation of classes with complex attributes and methods in object oriented databases.
Adrian Sergiu Dărăbant, Alina Câmpan, Grigor Moldovan, Horea Adrian Greblă · 2004
Abstract – Horizontal fragmentation plays an important role in the design phase of Distributed Databases. Complex class relationships: associations, aggregations and complex methods, require fragmentation algorithms to take into account the new problem dimensions induced by these features of the object oriented models. We propose in this paper a new method for horizontal partitioning of classes with complex attributes and methods, using AI clustering techniques. We provide quality and performance evaluations using a partition evaluator function and we prove that fragmentation methods handling complex interclass links produce better results than those ignoring these aspects. 1.