Mixed-criticality Task Models

Mixed-Criticality Task Models is a computational modeling framework that distinguishes itself within task models by enabling the simultaneous representation and scheduling of tasks with differing levels of criticality, typically to support correct operation across multiple assurance levels in real-time embedded systems.

34

Publications

1.1K

Citations

64

Authors

40

Institutions

Publications per year

2017–2026

14

Authors

64

  1. DZ
    Dakai Zhu

    The University of Texas at San Antonio, United States

    6 publications · 318 citations

    6

    h-index

  2. HS
    Hang Su

    The University of Texas at San Antonio, United States

    6 publications · 318 citations

    6

    h-index

  3. SB
    Sanjoy Baruah

    University of North Carolina at Chapel Hill, United States

    5 publications · 166 citations

    5

    h-index

  4. ZG
    Zhishan Guo

    University of Central Florida, United States

    4 publications · 168 citations

    4

    h-index

  5. RM
    Roberto Medina

    Universidad de Valladolid, Spain

    3 publications · 65 citations

    3

    h-index

1–5 of 64

Venues

  1. Journal of Systems Architecture

    JSA · 2 publications · 88 citations

    2

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  2. IEEE Transactions on Computers

    2 publications · 61 citations

    2

    h-index

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

    Repository · 2 publications · 39 citations

    2

    h-index

  4. 2

    h-index

  5. IEEE Access

    1 publications · 25 citations

    1

    h-index

1–5