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Revisiting Size-Based Scheduling with Estimated Job Sizes by Dell'Amico, Matteo; Carra, Damiano; Pastorelli, Mario; Michiardi, Pietro is a scholarly article available to read on EtoBox.

What is Revisiting Size-Based Scheduling with Estimated Job Sizes about?

We study size-based schedulers, and focus on the impact of inaccurate job size information on response time and fairness. Our intent is to revisit previous results, which allude to performance degradation for even small errors on job size estimates, thus limiting the applicability of size-based schedulers. We show that scheduling performance is tightly connected to workload characteristics: in the absence of large skew in the job size distribution, even extremely imprecise estimates suffice to outperform size-oblivious disciplines. Instead, when job sizes are heavily skewed, known size-based disciplines suffer. In this context, we show -- for the first time -- the dichotomy of over-estimation versus under-estimation. The former is, in general, less problematic than the latter, as its effects are localized to individual jobs. Instead, under-estimation leads to severe problems that may affect a large number of jobs. We present an approach to mitigate these problems: our technique requires no complex modifications to original scheduling policies and performs very well. To support our claim, we proceed with a simulation-based evaluation that covers an unprecedented large parameter spac

Author

Dell'Amico, Matteo; Carra, Damiano; Pastorelli, Mario; Michiardi, Pietro

Published

2014

Language

EN