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Abstract: We explore the performance of an M/GI/1 queue under various scheduling policies from the perspective of a new metric: the slowdown experienced by largest jobs. We consider scheduling policies that bias against large jobs, towards large jobs, and those that are fair, e.g., Processor-Sharing. We prove that as job size increases to infinity, all work conserving policies converge almost surely with respect to this metric to no more than denotes load. We also find that the expected... (Update)
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BibTeX entry: (Update)
@misc{ harchol-balter-asymptotic,
author = "Mor Harchol-Balter and Karl Sigman and Adam Wierman",
title = "Asymptotic Convergence of Scheduling Policies with Respect to Slowdown",
url = "citeseer.ist.psu.edu/article/harchol-balter02asymptotic.html" }
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