An enhanced grouping algorithm for vertical partitioning problem in DDBs

Distribution design involves making decisions on the fragmentation and allocation of data across the sites of a computer network. Vertical partitioning is the process of subdividing the attributes of a relation to generate fragments. In this paper, we propose an enhancement to our previous work for vertical partitioning algorithm using grouping approach. This algorithm starts from the attribute affinity matrix and generates initial groups based on the affinity values between attributes. Then, it attempts to merge the initial groups to produce final groups that will represent the fragments.