Disk subsystem load balancing: disk striping vs. conventional data placement

To provide improved input/output performance, as well as to accommodate growing storage requirements, disk subsystems are increasing in size. A major hurdle to obtaining the performance available from these large disk subsystems is load imbalance, or disk skew. Dynamic data placement, the conventional load balancing technique, is usually adequate to deal with load imbalance because it is forced to accept atomic data sets with rapidly changing access patterns. The authors name this rapid fluctuation ´floating load imbalance´ and distinguish it from the conventional view of load imbalance, referred to as ´fixed load imbalance´. Disk striping at a high granularity is suggested as a solution to floating load imbalance, the atomic data set problem and the complexity of balancing large disk subsystems. Disk striping uniformly spreads data sets across the disks in the subsystem and essentially randomizes, the disk accessed by each request. This randomization effectively handles both fixed and floating load imbalance.