NDLI: IO Tetris: Deep Storage Consolidation for the Cloud via Fine-Grained Workload Analysis

Content Provider	IEEE Xplore Digital Library
Author	Rui Zhang Routray, R. Eyers, D.M. Chambliss, D. Sarkar, P. Willcocks, D. Pietzuch, P.
Copyright Year	2011
Abstract	Intelligent workload consolidation in storage systems leads to better Return On Investment (ROI), in terms of more efficient use of data center resources, better Quality of Service (QoS), and lower power consumption. This is particularly significant yet challenging in a cloud environment, in which a large set of different workloads multiplex on a shared, heterogeneous infrastructure. However, the increasing availability of fine grained workload logging facilities allows better insights to be gained from workload profiles. As a consequence, consolidation can be done more deeply, according to a detailed understanding of how well given workloads mix. We describe IO Tetris, which takes a first look at fine-grained consolidation in large-scale storage systems by leveraging temporal patterns found in real-world I/O traces gathered from enterprise storage environments. The core functionality of IO Tetris consists of two stages. A grouping stage performs hierarchical grouping of storage workloads to find complementary groupings that consolidate well together over time and conflicting ones that do not. After that, a migration stage examines the discovered groupings to determine how to maximize resource utilization efficiency while minimizing migration costs. Experiments based on customer I/O traces from a high-end enterprise class IBM storage controller show that a non-trivial number of IO Tetris groupings exist in real-world storage workloads, and that these groupings can be leveraged to achieve better storage consolidation in a cloud setting.
Starting Page	700
Ending Page	707
File Size	1243683
Page Count	8
File Format	PDF
ISBN	9781457708367
ISSN	21596190
DOI	10.1109/CLOUD.2011.103
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Performance evaluation Cloud computing Correlation Sensitivity Storage Consolidation Service Provider Migration Cloud Servers Data Center Optimization
Content Type	Text
Resource Type	Article

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