An optimal workload-based data allocation approach for multidisk databases

Parallel processing mechanisms and data layout approaches that significantly affect access performance of database systems have received increased attention in the last few decades. Multidisk allocation problems try to find an allocation of relations to disks such that expected query cost is minimized. Solving this NP-complete problem is extremely time-consuming, especially because the need for solution time rises exponentially as the number of 0–1 variables increases. This study presents a novel and efficient approach for deriving an optimal layout of relations on disks based on database statistics of access patterns and relation sizes. In addition to minimizing query cost, the proposed model allows replication of relations, minimizes storage cost, and enhances computational efficiency by reducing the number of 0–1 variables and constraints. Illustrative examples and experimental results demonstrate the advantages and efficiency of the proposed method.