Computationally intensive workloads continue to dominate the use of
large-scale clusters at universities and research labs where thousands of
batch jobs are submitted everyday. Recent advances in grid technologies
promise to push these batch workloads into shared infrastructures such as
hosting centers. In this environment user value, which corresponds to
currency, and scheduling to maximize user value becomes the primary goal.
Recent work \cite{millennium} has shown that scheduling based on
user-defined per job valuations improves aggregate system value when
compared with common scheduling policies. Job valuations specify differing
user values for a range of performance levels. In this work we examine
scheduling based on per job user-defined valuations. We show that the
valuations used in \cite{millennium} provide a simple, rich, and tractable
formulation for value-based scheduling. This is significant because even
simple formulations of value can prove intractable to schedule. We also
show how value-based scheduling, when viewed as a common currency, can
facilitate batch computation on shared infrastructures by using multiple
competing batch markets.
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