Abstract
We consider the speed scaling problem where the quality of service objective is deadline feasibility and the power objective is temperature. In the case of batched jobs, we give a simple algorithm to compute the optimal schedule. For general instances, we give a new online algorithm, and obtain an upper bound on the competitive ratio of this algorithm that is an order of magnitude better than the best previously known bound upper bound on the competitive ratio for this problem.
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Atkins, L., Aupy, G., Cole, D., Pruhs, K. (2011). Speed Scaling to Manage Temperature. In: Marchetti-Spaccamela, A., Segal, M. (eds) Theory and Practice of Algorithms in (Computer) Systems. TAPAS 2011. Lecture Notes in Computer Science, vol 6595. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19754-3_4
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DOI: https://doi.org/10.1007/978-3-642-19754-3_4
Publisher Name: Springer, Berlin, Heidelberg
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