NDLI: Entropy: a consolidation manager for clusters

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Entropy: a consolidation manager for clusters

Content Provider	ACM Digital Library
Author	Lorca, Xavier Lawall, Julia Hermenier, Fabien Muller, Gilles Menaud, Jean-Marc
Abstract	Clusters provide powerful computing environments, but in practice much of this power goes to waste, due to the static allocation of tasks to nodes, regardless of their changing computational requirements. Dynamic consolidation is an approach that migrates tasks within a cluster as their computational requirements change, both to reduce the number of nodes that need to be active and to eliminate temporary overload situations. Previous dynamic consolidation strategies have relied on task placement heuristics that use only local optimization and typically do not take migration overhead into account. However, heuristics based on only local optimization may miss the globally optimal solution, resulting in unnecessary resource usage, and the overhead for migration may nullify the benefits of consolidation. In this paper, we propose the Entropy resource manager for homogeneous clusters, which performs dynamic consolidation based on constraint programming and takes migration overhead into account. The use of constraint programming allows Entropy to find mappings of tasks to nodes that are better than those found by heuristics based on local optimizations, and that are frequently globally optimal in the number of nodes. Because migration overhead is taken into account, Entropy chooses migrations that can be implemented efficiently, incurring a low performance overhead.
Starting Page	41
Ending Page	50
Page Count	10
File Format	PDF
ISBN	9781605583754
DOI	10.1145/1508293.1508300
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2009-03-11
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Migration Cluster Dynamic consolidation Virtualization Reconfiguration
Content Type	Text
Resource Type	Article

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