Publication
ICAC 2005
Conference paper

Utility-function-driven resource allocation in autonomic systems

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Abstract

We study autonomic resource allocation among multiple applications based on optimizing the sum of utility for each application. We compare two methodologies for estimating the utility of resources: a queuing-theoretic performance model and model-free reinforcement learning. We evaluate them empirically in a distributed prototype data center and highlight tradeoffs between the two methods.

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Publication

ICAC 2005

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