SLAS

Abstract

Round-robin striping, due to its uniform distribution and low-complexity computation, is widely used by applications which demand high bandwidth and massive storage. Because many systems are nonstoppable when their storage capacity and I/O bandwidth need increasing, an efficient and online mechanism to add more disks to striped volumes is very important. In this article, it is presented and proved that during data redistribution caused by scaling a round-robin striped volume, there is always a reordering window where data consistency can be maintained while changing the order of data movements. Furthermore, by exploiting the reordering window characteristic, SLAS is proposed to scale round-robin striped volumes, which reduces the cost of data redistribution effectively. First, SLAS applies a new mapping management solution based on a sliding window to support data redistribution without loss of scalability; second, it uses lazy updates of mapping metadata to decrease the number of metadata writes required by data redistribution; third, it changes the order of data chunk movements to aggregate reads/writes of data chunks. Our results from detailed simulations using real-system workloads show that, compared with the traditional approach, SLAS can reduce redistribution duration by up to 40.79% with similar maximum response time of foreground I/Os. Finally, our discussion indicates that the SLAS approach works for both disk addition and disk removal to/from striped volumes.