Online bandwidth allocation

  • Authors:

  • Michal Forišek;Branislav Katreniak;Jana Katreniaková;Rastislav Královič;Richard Královič;Vladimír Koutný;Dana Pardubská;Tomáš Plachetka;Branislav Rovan

  • Affiliations:

  • Dept. of Computer Science, Comenius University, Bratislava, Slovakia;Dept. of Computer Science, Comenius University, Bratislava, Slovakia;Dept. of Computer Science, Comenius University, Bratislava, Slovakia;Dept. of Computer Science, Comenius University, Bratislava, Slovakia;Dept. of Computer Science, Comenius University, Bratislava, Slovakia and Dept. of Computer Science, ETH Zürich, Switzerland;Dept. of Computer Science, Comenius University, Bratislava, Slovakia;Dept. of Computer Science, Comenius University, Bratislava, Slovakia;Dept. of Computer Science, Comenius University, Bratislava, Slovakia;Dept. of Computer Science, Comenius University, Bratislava, Slovakia

  • Venue:
  • ESA'07 Proceedings of the 15th annual European conference on Algorithms
  • Year:
  • 2007

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Abstract

The paper investigates a version of the resource allocation problem arising in the wireless networking, namely in the OVSF code reallocation process. In this setting a complete binary tree of a given height n is considered, together with a sequence of requests which have to be served in an online manner. The requests are of two types: an insertion request requires to allocate a complete subtree of a given height, and a deletion request frees a given allocated subtree. In order to serve an insertion request it might be necessary to move some already allocated subtrees to other locations in order to free a large enough subtree. We are interested in the worst case average number of such reallocations needed to serve a request. In [4] the authors delivered bounds on the competitive ratio of online algorithm solving this problem, and showed that the ratio is between 1.5 and O(n). We partially answer their question about the exact value by giving an O(1)-competitive online algorithm. In [3], authors use the same model in the context of memory management systems, and analyze the number of reallocations needed to serve a request in the worst case. In this setting, our result is a corresponding amortized analysis.