Probabilistic Schedulability

Probabilistic Schedulability is a schedulability analysis framework that characterizes the likelihood of a task set meeting its deadlines under uncertainty by modeling task execution times, arrival patterns, or environmental conditions as stochastic variables.

32

Publications

1.3K

Citations

73

Authors

45

Institutions

Publications per year

2017–2026

5

Authors

73

  1. LC
    Liliana Cucu‐Grosjean

    Institut national de recherche en sciences et technologies du numérique, France

    7 publications · 227 citations

    7

    h-index

  2. LS
    Luca Santinelli

    Office National d'Études et de Recherches Aérospatiales, France

    4 publications · 107 citations

    4

    h-index

  3. DM
    Dorin Maxim

    Institut national de recherche en sciences et technologies du numérique, France

    3 publications · 100 citations

    3

    h-index

  4. AB
    Alan Burns

    University of York, United Kingdom

    3 publications · 348 citations

    3

    h-index

  5. LA
    Luca Abeni

    Scuola Superiore Sant'Anna, Italy

    2 publications · 128 citations

    2

    h-index

1–5 of 73

Venues

  1. Formal Aspects of Computing

    1 publications · 17 citations

    1

    h-index

  2. IEEE Transactions on Industrial Informatics

    1 publications · 13 citations

    1

    h-index

  3. 1

    h-index

  4. 1

    h-index

  5. Deep Blue (University of Michigan)

    Repository · 1 publications · 32 citations

    1

    h-index

1–5