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  • 标题:Optimal Lower Bounds for Distributed and Streaming Spanning Forest Computation
  • 本地全文:下载
  • 作者:Jelani Nelson ; Huacheng Yu
  • 期刊名称:Electronic Colloquium on Computational Complexity
  • 印刷版ISSN:1433-8092
  • 出版年度:2018
  • 卷号:2018
  • 出版社:Universität Trier, Lehrstuhl für Theoretische Computer-Forschung
  • 摘要:

    We show optimal lower bounds for spanning forest computation in two different models:

    * One wants a data structure for fully dynamic spanning forest in which updates can insert or delete edges amongst a base set of n vertices. The sole allowed query asks for a spanning forest, which the data structure should successfully answer with some given (potentially small) constant probability 0"> 0 . We prove that any such data structure must use ( n log 3 n ) bits of memory.

    * There is a referee and n vertices in a network sharing public randomness, and each vertex knows only its neighborhood; the referee receives no input. The vertices each send a message to the referee who then computes a spanning forest of the graph with constant probability 0"> 0 . We prove the average message length must be ( log 3 n ) bits.

    Both our lower bounds are optimal, with matching upper bounds provided by the AGM sketch \cite{AhnGM12} (which even succeeds with probability 1 − 1 pol y ( n ) ). Furthermore, for the first setting we show optimal lower bounds even for low failure probability , as long as 2^{-n^{1-\epsilon}}"> 2 − n 1 − .

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