Probabilistic Self-stabilization

Probabilistic Self-Stabilization is a form of self-stabilization in distributed systems where, starting from any arbitrary state, the system is guaranteed to converge to a legitimate state with probability one, rather than in a deterministic manner, thereby distinguishing it from classical self-stabilization through its reliance on probabilistic transitions and fairness assumptions.

10

Publications

290

Citations

27

Authors

25

Institutions

Publications per year

2017–2026

2

Authors

27

  1. ST
    Sébastien Tixeuil

    Sorbonne Université, France

    3 publications · 114 citations

    3

    h-index

  2. MG
    Maria Gradinariu

    University of Nevada, Las Vegas, United States

    2 publications · 69 citations

    2

    h-index

  3. SM
    Stéphane Messika

    Laboratoire de Recherche en Informatique, France

    1 publications · 22 citations

    1

    h-index

  4. EN
    Emanuele Natale

    University of Rome Tor Vergata, Italy

    1 publications · 12 citations

    1

    h-index

  5. JC
    Julien Clément

    Centre National de la Recherche Scientifique, France

    1 publications · 22 citations

    1

    h-index

1–5 of 27

Venues

  1. Theoretical Computer Science

    1 publications · 18 citations

    1

    h-index

  2. Stochastic Processes and their Applications

    1 publications · 15 citations

    1

    h-index

  3. Formal Aspects of Computing

    1 publications · 46 citations

    1

    h-index

  4. Electronic workshops in computing

    1 publications · 50 citations

    1

    h-index

1–4