Utility-Function-Driven Resource Allocation in Autonomic Systems
G. Tesauro, R. Das, William E. Walsh, Jeffrey O. Kephart · 2005
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