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@InProceedings{AMACS07,
  author =	 "Jonathan Wildstrom and Peter Stone and Emmett
                  Witchel",
  title =	 "Autonomous Return on Investment Analysis of
                  Additional Processing Resources",
  booktitle =	 "2007 Workshop on Adaptive Methods in Autonomic
                  Computing Systems",
  month =	 "June",
  year =	 2007,
  abstract =	 { As the use of virtualization and partitioning
                  grows, it becomes possible to deploy a multi-tier
                  web-based application with a variable amount of
                  computing power. This introduces the possibility of
                  provisioning only for a minimum workload, with the
                  intention of renting more resources as necessary,
                  but it also creates the problem of quickly and
                  accurately identifying when more resources are
                  needed or unneeded resources are being paid
                  for. This paper presents a machine learning based
                  approach to handling this problem. An autonomous
                  adaptive agent learns to predict the gain (or loss)
                  that would result from more (or less) resources;
                  this agent uses only low-level system statistics,
                  rather than relying on custom instrumentation of the
                  operating system or middleware. Our agent is fully
                  implemented and evaluated on a publicly available
                  multi-machine, multi-process distributed system (the
                  online transaction processing benchmark TPC-W). We
                  show that our adaptive agent is competitive with any
                  static choice of computing resources over a variety
                  of test workloads. We also show that the agent
                  outperforms each static choice in at least one case,
                  implying that it is well suited for a situation
                  where the workload is unknown.  },
  wwwnote =	 {<A HREF="http://research.ihost.com/amacs07/</A>},
}