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  1. Transactions on Computation Theory (TOCT)
  2. ACM Transactions on Computation Theory (TOCT) : Volume 3
  3. Issue 2, January 2012
  4. The Value of Multiple Read/Write Streams for Approximating Frequency Moments
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ACM Transactions on Computation Theory (TOCT) : Volume 9
ACM Transactions on Computation Theory (TOCT) : Volume 8
ACM Transactions on Computation Theory (TOCT) : Volume 7
ACM Transactions on Computation Theory (TOCT) : Volume 6
ACM Transactions on Computation Theory (TOCT) : Volume 5
ACM Transactions on Computation Theory (TOCT) : Volume 4
ACM Transactions on Computation Theory (TOCT) : Volume 3
Issue 2, January 2012
Pebbles and Branching Programs for Tree Evaluation
Three-Query Locally Decodable Codes with Higher Correctness Require Exponential Length
The Value of Multiple Read/Write Streams for Approximating Frequency Moments
Issue 1, August 2011
ACM Transactions on Computation Theory (TOCT) : Volume 2
ACM Transactions on Computation Theory (TOCT) : Volume 1

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The Value of Multiple Read/Write Streams for Approximating Frequency Moments

Content Provider ACM Digital Library
Author Beame, Paul Huynh, Trinh
Copyright Year 2012
Abstract We consider the read/write streams model, an extension of the standard data stream model in which an algorithm can create and manipulate multiple read/write streams in addition to its input data stream. Like the data stream model, the most important parameter for this model is the amount of internal memory used by such an algorithm. The other key parameters are the number of streams the algorithm uses and the number of passes it makes on these streams. We consider how the addition of multiple streams impacts the ability of algorithms to approximate the frequency moments of the input stream. We show that any randomized read/write stream algorithm with a fixed number of streams and a sublogarithmic number of passes that produces a constant factor approximation of the $\textit{k}-th$ frequency moment $F_{k}$ of an input sequence of length of at most $\textit{N}$ from {1,..., $\textit{N}}$ requires space $\textit{Ω}(\textit{N}$ $^{1™4/k™Δ})$ for any $\textit{Δ} > 0.$ For comparison, it is known that with a single read-only one-pass data stream there is a randomized constant-factor approximation for $F_{k}$ using $Õ(N^{1™2/k})$ space, and that by sorting, which can be done deterministically in $\textit{O}(log$ $\textit{N})$ passes using 3 read/write streams, $F_{k}$ can be computed exactly. Therefore, although the ability to manipulate multiple read/write streams can add substantial power to the data stream model, with a sublogarithmic number of passes this does not significantly improve the ability to approximate higher frequency moments efficiently. We obtain our results by showing a new connection between the read/write streams model and the multiparty number-in-hand communication model.
Starting Page 1
Ending Page 22
Page Count 22
File Format PDF
ISSN 19423454
e-ISSN 19423462
DOI 10.1145/2077336.2077339
Volume Number 3
Issue Number 2
Journal ACM Transactions on Computation Theory (TOCT)
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2012-01-01
Publisher Place New York
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Data streams Communication complexity External-memory algorithms Frequency moments Read/write streams
Content Type Text
Resource Type Article
Subject Computational Theory and Mathematics Theoretical Computer Science
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