Stream Computation

Stream Computation is a computational paradigm that processes continuous, ordered sequences of data elements in real-time or near real-time, typically with constraints on memory and processing time, distinguishing it from batch computation by its incremental and often irreversible processing of unbounded data streams.

256

Publications

17.6K

Citations

664

Authors

257

Institutions

Publications per year

2017–2026

51

Authors

664

  1. GC
    Graham Cormode

    AT&T (United States), United States

    6 publications · 452 citations

    6

    h-index

  2. WJ
    William J. Dally

    Stanford University, United States

    6 publications · 809 citations

    6

    h-index

  3. DP
    David P. Woodruff

    IBM Research - Almaden, United States

    6 publications · 476 citations

    6

    h-index

  4. JD
    John D. Owens

    University of California, Davis, United States

    5 publications · 772 citations

    5

    h-index

  5. UJ
    Ujval J. Kapasi

    Stanford University, United States

    5 publications · 772 citations

    5

    h-index

1–5 of 664

Venues

  1. Theoretical Computer Science

    5 publications · 169 citations

    5

    h-index

  2. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)

    Repository · 5 publications · 84 citations

    5

    h-index

  3. IEEE Transactions on Parallel and Distributed Systems

    TPDS · 4 publications · 178 citations

    4

    h-index

  4. Journal of Parallel and Distributed Computing

    3 publications · 74 citations

    3

    h-index

  5. ACM SIGPLAN Notices

    3 publications · 65 citations

    3

    h-index

1–5