Preemptive scheduling in overloaded systems

Authors:
Marek Chrobak;Leah Epstein;John Noga;Jiří Sgall;Rob van Stee;Tomáš Tichý;Nodari Vakhania
Affiliations:
Department of Computer Science, University of California, Riverside, CA;School of Computer Science, The Interdisciplinary Center, P.O.B. 167, 46150 Herzliya, Israel;Department of Computer Science, California State University, Northridge, CA;Mathematical Institute, AS CR, Zitná 25, CZ-11567 Praha 1, Czech Republic;Institut für Informatik, Albert-Ludwigs-Universität, Georges-Köhler-Allee, 79110, Freiburg, Germany;Mathematical Institute, AS CR, Zitná 25, CZ-11567 Praha 1, Czech Republic;Facultad de Ciencias, Universidad Autonoma del Estado de Morelos, 62251 Cuernavaca, Morelos, Mexico
Venue:
Journal of Computer and System Sciences
Year:
2003

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Abstract

The following scheduling problem is studied: We are given a set of tasks with release times, deadlines, and profit rates. The objective is to determine a 1-processor preemptive schedule of the given tasks that maximizes the overall profit. In the standard model, each completed task brings profit, while noncompleted tasks do not. In the metered model, a task brings profit proportional to the execution time even if not completed. For the metered task model, we present an efficient offline algorithm and improve both the lower and upper bounds on the competitive ratio of online algorithms. Furthermore, we prove three lower bound results concerning resource augmentation in both models.