Abstract
We examine the worst-case performance of a class of heuristic scheduling algorithms commonly referred to as priority-driven or list-scheduling algorithms. It is well known that these algorithms have anomalous, unpredictable performance when used to schedule nonpreemptive tasks with precedence constraints. We present a general method for deriving the worst-case performance of these algorithms. This method is easy to use, yet powerful enough to yield tight performance bounds for many classes of scheduling problems. We demonstrate the method for several problems to show it has wide applicability. We also present several task systems for which list-scheduling algorithms exhibit unavoidable worst-case performance and discuss the general characteristics of these task systems. These task systems are sometimes overlooked in simulation studies; consequently, the results of these studies may be overly optimistic.
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This work was partially supported by the US Navy. ONR Contract No. NVY N0001489 J1181
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Gillies, D.W., Liu, J.W.S. Greed in resource scheduling. Acta Informatica 28, 755–775 (1991). https://doi.org/10.1007/BF01261655
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DOI: https://doi.org/10.1007/BF01261655