New Approaches to Optimization and Utility Elicitation in Autonomic Computing

Relu Patrascu, Craig Boutilier
Department of Computer Science
University of Toronto
Toronto, ON M5S 3H5
email: relu,

Rajarshi Das, Jeffrey O. Kephart, Gerald Tesauro, William E. Walsh
IBM T. J. Watson Research Center
19 Skyline Dr.
Hawthorne, NY 10532, USA
email: rajarshi,kephart,gtesauro,

Autonomic (self-managing) computing systems face the critical problem of resource allocation to different computing elements. Adopting a recent model, we view the problem of provisioning resources as involving utility elicitation and optimization to allocate resources given imprecise utility information. In this paper, we propose a new algorithm for regret-based optimization that performs significantly faster than that proposed in earlier work. We also explore new regret-based elicitation heuristics that are able to find near-optimal allocations while requiring a very small amount of utility information from the distributed computing elements. Since regret-computation is intensive, we compare these to the more tractable Nelder-Mead optimization technique w.r.t. amount of utility information required.

To appear, AAAI-05

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