Decomposing Workload Bursts for Efficient Storage Resource Management

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 increase...

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Bibliographic Details
Published in:IEEE transactions on parallel and distributed systems 2011-05, Vol.22 (5), p.860-873
Main Authors: Lanyue Lu, Varman, P J, Doshi, K
Format: Article
Language:English
Subjects:
Algorithm design and analysis
Algorithms
Analytical models
Bursting
Bursts
Computer simulation
Costs
Decomposition
Energy consumption
Energy management
Energy storage
graduated QoS
Linux
Performance analysis
Power system management
Resource management
Resources management
scheduling
Servers
storage system
Workload
Workload decomposition
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Summary: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.
ISSN:1045-9219
1558-2183
DOI:10.1109/TPDS.2010.129