Abstract
In this paper we consider non-preemptive online scheduling of jobs with release times and deadlines on heterogeneous processors with speed scaling. The power needed by processor i to run at speed s is assumed to be \(s^{\alpha _i}\), where the exponent \(\alpha _i\) is a constant that can be different for each processor. We require the jobs to have agreeable deadlines, i.e., jobs with later release times also have later deadlines. The aim is to minimize the energy used to complete all jobs by their deadlines. For the case where the densities of the jobs differ only within a factor of two and the same holds for their interval lengths, we present an algorithm with constant competitive ratio. For arbitrary densities and interval lengths, we achieve a competitive ratio that is poly-logarithmic in the ratio of maximum to minimum density and in the ratio of maximum to minimum interval length.
A. Alsughayyir—Partially supported by the Department of Computer Science of Taibah University in Medina.
T. Erlebach—Supported by a study leave granted by University of Leicester.
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Alsughayyir, A., Erlebach, T. (2017). Online Algorithms for Non-preemptive Speed Scaling on Power-Heterogeneous Processors. In: Gao, X., Du, H., Han, M. (eds) Combinatorial Optimization and Applications. COCOA 2017. Lecture Notes in Computer Science(), vol 10628. Springer, Cham. https://doi.org/10.1007/978-3-319-71147-8_32
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