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Autonomic Computing, International Conference on (2005)
Seattle, Washington
June 13, 2005 to June 16, 2005
ISBN: 0-7965-2276-9
pp: 339-340
David Vengerov , Sun Microsystems Laboratories
Nikolai Iakovlev , Sun Microsystems Laboratories
ABSTRACT
This paper addresses the problem of dynamic resource allocation among multiple entities sharing a common set of resources. A solution approach is presented based on combining the reinforcement learning methodology with function approximation architectures. An implementation of this approach in Solaris 10 demonstrated a robust near-optimal performance on a simple problem of transferring CPUs among resource partitions so as to match the stochastically changing workload in each partition, both for large and small CPU migration costs.
INDEX TERMS
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CITATION
David Vengerov, Nikolai Iakovlev, "A Reinforcement Learning Framework for Dynamic Resource Allocation: First Results.", Autonomic Computing, International Conference on, vol. 00, no. , pp. 339-340, 2005, doi:10.1109/ICAC.2005.4
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