Online deadline scheduling with bounded energy efficiency

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Abstract

Existing work on scheduling with energy concern has focused on minimizing the energy for completing all jobs or achieving maximum throughput [19, 2, 7, 13, 14]. That is, energy usage is a secondary concern when compared to throughput and the schedules targeted may be very poor in energy efficiency. In this paper, we attempt to put energy efficiency as the primary concern and study how to maximize throughput subject to a user-defined threshold of energy efficiency. We first show that all deterministic online algorithms have a competitive ratio at least Δ, where Δ is the max-min ratio of job size. Nevertheless, allowing the online algorithm to have a slightly poorer energy efficiency leads to constant (i.e., independent of Δ) competitive online algorithm. On the other hand, using randomization, we can reduce the competitive ratio to O(log Δ) without relaxing the efficiency threshold. Finally we consider a special case where no jobs are "demanding" and give a deterministic online algorithm with constant competitive ratio for this case. © Springer-Verlag Berlin Heidelberg 2007.

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APA

Chan, J. W. T., Lam, T. W., Mak, K. S., & Wong, P. W. H. (2007). Online deadline scheduling with bounded energy efficiency. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4484 LNCS, pp. 416–427). Springer Verlag. https://doi.org/10.1007/978-3-540-72504-6_38

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