Abstract
We study the advice complexity of online buffer management. Advice complexity measures the amount of information about the future that an online algorithm needs to achieve optimality or a good competitive ratio. We study the 2-valued buffer management problem in both preemptive and nonpreemptive models and prove lower and upper bounds on the number of bits required by an optimal online algorithm in either model. We also provide results that shed light on the ineffectiveness of advice to improve the competitiveness of the best online algorithm for nonpreemptive buffer management. © Springer-Verlag 2012.
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CITATION STYLE
Dorrigiv, R., He, M., & Zeh, N. (2012). On the advice complexity of buffer management. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7676 LNCS, pp. 136–145). Springer Verlag. https://doi.org/10.1007/978-3-642-35261-4_17
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