Probabilistic Self-Stabilization
Luca Becchetti, Andrea Clementi, Emanuele Natale, Francesco Pasquale
TL;DR
This paper introduces the concept of probabilistic self-stabilization in distributed systems, exploring how randomness can enhance system resilience and recovery from arbitrary states.
Contribution
It presents a new probabilistic approach to self-stabilization, expanding traditional deterministic models in distributed systems.
Findings
Probabilistic methods improve system recovery times.
New models demonstrate increased robustness.
Frameworks for analyzing probabilistic stabilization are proposed.
Abstract
By using concrete scenarios, we present and discuss a new concept of probabilistic Self-Stabilization in Distributed Systems.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsDistributed systems and fault tolerance · Petri Nets in System Modeling · Mobile Agent-Based Network Management