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Published June 2005 | metadata_only
Journal Article

Classifying scheduling policies with respect to higher moments of conditional response time


In addition to providing small mean response times, modern applications seek to provide users predictable service and, in some cases, Quality of Service (QoS) guarantees. In order to understand the predictability of response times under a range of scheduling policies, we study the conditional variance in response times seen by jobs of different sizes. We define a metric and a criterion that distinguish between contrasting functional behaviors of conditional variance, and we then classify large groups of scheduling policies.In addition to studying the conditional variance of response times, we also derive metrics appropriate for comparing higher conditional moments of response time across job sizes. We illustrate that common statistics such as raw and central moments are not appropriate when comparing higher conditional moments of response time. Instead, we find that cumulant moments should be used.

Additional Information

© 2005 ACM. Supported by NSF Career Grant CCR-0133077, NSF Theory CCR-0311383, NSF ITR CCR-0313148, IBM Corporation via Pittsburgh Digital Greenhouse Grant 2003, and a NSF Graduate Research Fellowship.

Additional details

August 22, 2023
August 22, 2023