We investigate the placement of N enterprise data-stores (e.g., database tables, application data) across an array of disks with the aim of minimizing the response time averaged over all served requests, while balancing the load evenly across all the disks in the parallel disk array. Incorporating the non-FCFS serving discipline and non work-conserving nature of disk drives in formulation of the placement problem is difficult and current placement strategies do not take them into account.

We present a novel formulation of the placement problem to incorporate these crucial features and identify the runlength of requests accessing a store as the most important criterion for placing the stores. We use these insights to design a fast (running time of N logN) placement algorithm that is optimal under the assumption that transfer times are small. Comprehensive experimental studies establish the efficacy of the proposed algorithm under a wide variety of workloads with the proposed algorithm reducing the response time for real storage traces by more than a factor of 2 under heterogeneous workload scenarios.