Name
Abstract | ||
|---|---|---|
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 infrastructure, management, and energy costs. We present a novel dynamic 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 dramatically 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 performance evaluation using several storage traces. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ICDCS.2009.55 | ICDCS |
Keywords | Field | DocType |
shared storage infrastructure,storage system,bursty nature,bursty workloads,storage service,recombination algorithm miser,decomposing bursts,storage workloads,increased infrastructure,storage trace,performance evaluation,tail wag,graduated qos,quality of service,schedules,data centers,scheduling,data center,distributed computing,qos,probability density function,multiplexing,resource allocation,performance,energy storage,probability distribution,servers,tail,data mining,resource management,resource manager,resource | Resource management,Converged storage,Computer science,Scheduling (computing),Server,Computer network,Quality of service,Provisioning,Schedule,Resource allocation,Distributed computing | Conference |
ISSN | Citations | PageRank |
1063-6927 | 12 | 0.59 |
References | Authors | |
17 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lanyue Lu | 1 | 101 | 5.67 |
| Peter J. Varman | 2 | 700 | 83.23 |
| Kshitij Doshi | 3 | 89 | 10.76 |