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Approximate counting: A detailed analysis

Published: 01 March 1985 Publication History

Abstract

Approximate counting is an algorithm proposed by R. Morris which makes it possible to keep approximate counts of large numbers in small counters. The algorithm is useful for gathering statistics of a large number of events as well as for applications related to data compression (Todd et al.). We provide here a complete analysis of approximate counting which establishes good convergence properties of the algorithm and allows to quantify precisely complexity-accuracy tradeoffs.

Bibliography

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L. Comtel,L'Analyse Combinatoire, 2 vol., P.U.F., Paris (1970).
[2]
G. Doetsch,Handbuch der Laplace Transformation, Birkhauser Verlag, Basel (1955).
[3]
P. Flajolet and N. Martin,Probabilistic counting, in Proc. 24th Annual Symp. on Foundations of Comp. Sc., Tucson, Arizona (1984), pp. 76–82.
[4]
R. G. Gallager,Variations on a theme by Huffmann, IEEE Trans. IT, 24 (1978) pp. 669–674.
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L. Kleinrock,Queuing Systems, Wiley Interscience, New York (1976).
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D. E. Knuth,The Art of Computer Programming: Sorting and Searching, Addison-Wesley, Reading (1973).
[7]
G. Langdon and J. Rissanen,Compression of black white images with binary arithmetic coding, IEEE Trans. on Communications (1981).
[8]
R. Morris,Counting large numbers of events in small registers, Comm. ACM, 21 (1978), pp. 840–842.
[9]
S. Todd, N. Martin, G. Langdon and D. Helman,Dynamic statistics collection for compression coding, Unpublished manuscript, 12 p. (1981).
[10]
E. T. Whittaker and G. N. Watson,A Course in Modern Analysis, (1907); 4th edition, Cambridge Univ. Press, 1927.

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      Reviews

      William J. J. Rey

      What is counting__?__ As we know, it consists in going from 0 to 1, from 1 to 2, and so forth; an increment of 1 is made at each step. But there are other possibilities; approximate counting consists of applying the increment with a probability p and no increment with probability 1? p. The counter state c exhibits a logarithmic characteristics, while p=exp(? ac). Analyzing this Markov process (formally, a discrete time pure birth process), the paper goes through a good piece of mathematics to derive with precision the expected value and variance of the counter state after n steps. It is good and interesting, although I wonder whether all minor technicalities had to be reported; rather, I would have appreciated a treatment less dedicated to the fact that p is exponential. “Approximate counting appears as the method of choice when a fairly constant relative accuracy is needed over a large range of values.”

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      Information & Contributors

      Information

      Published In

      cover image BIT
      BIT  Volume 25, Issue 1
      Mar 1985
      323 pages

      Publisher

      BIT Computer Science and Numerical Mathematics

      United States

      Publication History

      Published: 01 March 1985

      Author Tags

      1. Detailed Analysis
      2. Computational Mathematic
      3. Convergence Property
      4. Complete Analysis
      5. Data Compression

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      • (2024)A New Information Complexity Measure for Multi-pass Streaming with ApplicationsProceedings of the 56th Annual ACM Symposium on Theory of Computing10.1145/3618260.3649672(1781-1792)Online publication date: 10-Jun-2024
      • (2024)Efficient Wait-Free Linearizable Implementations of Approximate Bounded Counters Using Read-Write RegistersStructural Information and Communication Complexity10.1007/978-3-031-60603-8_18(318-335)Online publication date: 27-May-2024
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