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Kinesis: A new approach to replica placement in distributed storage systems

Kinesis: A new approach to replica placement in distributed storage systems Kinesis is a novel data placement model for distributed storage systems. It exemplifies three design principles: structure (division of servers into a few failure-isolated segments), freedom of choice (freedom to allocate the best servers to store and retrieve data based on current resource availability), and scattered distribution (independent, pseudo-random spread of replicas in the system). These design principles enable storage systems to achieve balanced utilization of storage and network resources in the presence of incremental system expansions, failures of single and shared components, and skewed distributions of data size and popularity. In turn, this ability leads to significantly reduced resource provisioning costs, good user-perceived response times, and fast, parallelized recovery from independent and correlated failures. This article validates Kinesis through theoretical analysis, simulations, and experiments on a prototype implementation. Evaluations driven by real-world traces show that Kinesis can significantly outperform the widely used Chain replica-placement strategy in terms of resource requirements, end-to-end delay, and failure recovery. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Storage (TOS) Association for Computing Machinery

Kinesis: A new approach to replica placement in distributed storage systems

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Publisher
Association for Computing Machinery
Copyright
Copyright © 2009 by ACM Inc.
ISSN
1553-3077
DOI
10.1145/1480439.1480440
Publisher site
See Article on Publisher Site

Abstract

Kinesis is a novel data placement model for distributed storage systems. It exemplifies three design principles: structure (division of servers into a few failure-isolated segments), freedom of choice (freedom to allocate the best servers to store and retrieve data based on current resource availability), and scattered distribution (independent, pseudo-random spread of replicas in the system). These design principles enable storage systems to achieve balanced utilization of storage and network resources in the presence of incremental system expansions, failures of single and shared components, and skewed distributions of data size and popularity. In turn, this ability leads to significantly reduced resource provisioning costs, good user-perceived response times, and fast, parallelized recovery from independent and correlated failures. This article validates Kinesis through theoretical analysis, simulations, and experiments on a prototype implementation. Evaluations driven by real-world traces show that Kinesis can significantly outperform the widely used Chain replica-placement strategy in terms of resource requirements, end-to-end delay, and failure recovery.

Journal

ACM Transactions on Storage (TOS)Association for Computing Machinery

Published: Jan 1, 2009

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