Streaming Data Processing

Streaming Data Processing is a computational paradigm that belongs to the class of data processing methods, distinguished by its capability to continuously ingest, analyze, and transform data streams in real time as they are generated, enabling low-latency decision-making in IoT analytics and reconfigurable accelerator systems.

673

Publications

32.4K

Citations

2.4K

Authors

711

Institutions

Publications per year

2017–2026

255

Authors

2.4K

  1. VG
    Vincenzo Gulisano

    Chalmers University of Technology, Sweden

    12 publications · 592 citations

    11

    h-index

  2. BG
    Buğra Gedik

    IBM (United States), United States

    12 publications · 655 citations

    11

    h-index

  3. HA
    Henrique Andrade

    IBM (United States), United States

    8 publications · 618 citations

    8

    h-index

  4. MP
    Marina Papatriantafilou

    Chalmers University of Technology, Sweden

    8 publications · 139 citations

    8

    h-index

  5. NT
    Nesime Tatbul

    Intel (United States), United States

    7 publications · 3K citations

    7

    h-index

1–5 of 2.4K

Venues

  1. Proceedings of the VLDB Endowment

    PVLDB · 14 publications · 794 citations

    13

    h-index

  2. IEEE Access

    15 publications · 507 citations

    13

    h-index

  3. Future Generation Computer Systems

    FGCS · 11 publications · 672 citations

    11

    h-index

  4. Journal of Parallel and Distributed Computing

    9 publications · 180 citations

    9

    h-index

  5. Sensors

    8 publications · 244 citations

    8

    h-index

1–5