Scheduling and Data Replication to Improve Tape Jukebox Performance

An increasing number of database applications require on-line access to massive amounts of data. Since large-scale storage systems implemented entirely on magnetic disk can be impractical or too costly for many applications, tape jukeboxes can provide an attractive solution. Unfortunately, current implementations of tape jukeboxes deliver poor performance for applications that access data randomly. This paper shows how the performance shortcomings of tape jukeboxes can be improved across a broad parameter space via a new scheduling algorithm and schemes for the placement and replication of hot data. We substantiate our claim by an extensive simulation study that quantifies the improvements obtained over a wide variety of workload characteristics.