Efficient disk replacement and data migration algorithms for large disk subsystems

Abstract

Random data placement, which is efficient and scalable for large-scale storage systems, has recently emerged as an alternative to traditional data striping. In this report, we study the disk replacement problem (DRP) to find a sequence of disk additions and removals for a storage system, while migrating the data and respecting the following constraints: (1) the data is initially balanced across the existing distributed disk configuration, (2) the data must again be balanced across the new configuration, and (3) the data migration cost must be minimized. In practice, migrating data from old disks to new devices is complicated by the fact that the total number of disks connected to the storage system is often limited by a fixed number of available slots and not all the old and new disks can be connected at the same time. This article presents solutions for both cases where the number of disk slots is either unconstrained or constrained.