Issue No.05 - May (2011 vol.22)
Lanyue Lu , Rice University, Houston
Peter J. Varman , Rice University, Houston
Kshitij Doshi , Intel Corporation, Chandler
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TPDS.2010.129
The growing popularity of hosted storage services and shared storage infrastructure in data centers is driving the recent interest in resource management and QoS in storage systems. The bursty nature of storage workloads raises significant performance and provisioning challenges, leading to increased resource requirements, management costs, and energy consumption. We present a novel workload shaping framework to handle bursty workloads, where the arrival stream is dynamically decomposed to isolate its bursts, and then rescheduled to exploit available slack. We show how decomposition reduces the server capacity requirements and power consumption significantly, while affecting QoS guarantees minimally. We present an optimal decomposition algorithm RTT and a recombination algorithm Miser, and show the benefits of the approach by evaluating the performance of several storage workloads using both simulation and Linux implementation.
Workload decomposition, graduated QoS, storage system, resource management, scheduling.
Lanyue Lu, Peter J. Varman, Kshitij Doshi, "Decomposing Workload Bursts for Efficient Storage Resource Management", IEEE Transactions on Parallel & Distributed Systems, vol.22, no. 5, pp. 860-873, May 2011, doi:10.1109/TPDS.2010.129