Optimization approach for data allocation in multidisk database

In the last decade, many parallel process mechanisms have been developed in information systems for enhancing their performance. But I/O throughput rates are still the bottleneck for data processing in the systems. In particular, relational database systems encounter this performance problem dealing with expensive operations such as the join operation. To treat a class of two-way join problems in database, Rotem et al. proposed a linearization method for finding the optimal allocation of relations to multidisk database such that the expected query cost is minimized. For the multidisk allocation problem with N relations and M disks, their model needs MN+N(N−1)/2+MN(N−1)/2 0–1 variables. This paper proposes a concise method to reformulate the same problem, which requires only MN+N(N−1)/2 0–1 variables. The problem can hence be more efficiently solved by the concise method. The analytical superiority of the concise method in terms of the number of iterations and execution times can be seen, through a computational experiment conducted on a set of generated test examples.