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Sliding Window Algorithms

  • Reference work entry
  • First Online:
Encyclopedia of Algorithms

  • 634 Accesses

Years and Authors of Summarized Original Work

  • 2007; Braverman, Ostrovsky

Problem Definition

In the last decade, the theoretical study of the sliding window model was developed to advance applications with very large input and time-sensitive output. In some practical situations, input might be seen as an ordered sequence, and it is useful to restrict computations to recent portions of the input. Examples include the analysis of recent tweets and time series of the stock market. To address the aforementioned practical situations, Datar et al. [20] introduced the sliding window model that assumes that the input is a stream (i.e., the ordered sequence) of data elements and divides the data elements into two categories: active elements and expiredelements. Typically, a recent portion (i.e., a suffix) of the stream defines the window of active elements, and the reminder (i.e., a complimenting prefix) of the stream defines the set of expired elements. When a new data element arrives, the...

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Acknowledgements

This material is based upon work supported in part by the National Science Foundation under Grant No. 1447639.

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Authors and Affiliations

  1. Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA

    Vladimir Braverman

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  1. Vladimir Braverman
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Correspondence to Vladimir Braverman .

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Editors and Affiliations

  1. Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL, USA

    Ming-Yang Kao

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Braverman, V. (2016). Sliding Window Algorithms. In: Kao, MY. (eds) Encyclopedia of Algorithms. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2864-4_797

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