A belated proof of self-stabilization
Distributed Computing
An exercise in proving self-stabilization with a variant function
Information Processing Letters
Information Processing Letters
Stabilizing Communication Protocols
IEEE Transactions on Computers - Special issue on protocol engineering
ACM Computing Surveys (CSUR)
Introduction to distributed algorithms
Introduction to distributed algorithms
A simplified proof for a self-stabilizing protocol: a game of cards
Information Processing Letters
Guarded commands, nondeterminacy and formal derivation of programs
Communications of the ACM
Self-stabilizing systems in spite of distributed control
Communications of the ACM
Theoretical Foundations of Computer Sciences
Theoretical Foundations of Computer Sciences
An exercise in proving convergence through transfer functions
ICDCS '99 Workshop on Self-stabilizing Systems
ICPADS '06 Proceedings of the 12th International Conference on Parallel and Distributed Systems - Volume 1
A note on K-state self-stabilization in a ring with K = N
Nordic Journal of Computing
Stabilization in dynamic systems with varying equilibrium
SSS'07 Proceedings of the 9h international conference on Stabilization, safety, and security of distributed systems
r-semi-groups: a generic approach for designing stabilizing silent tasks
SSS'07 Proceedings of the 9h international conference on Stabilization, safety, and security of distributed systems
A tranformational approach for designing scheduler-oblivious self-stabilizing algorithms
SSS'10 Proceedings of the 12th international conference on Stabilization, safety, and security of distributed systems
Towards automatic convergence verification of self-stabilizing algorithms
SSS'05 Proceedings of the 7th international conference on Self-Stabilizing Systems
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A particularly suitable design strategy for constructing a robust distributed algorithm is to endow it with a self-stabilization property. Such a property guarantees that the system will always return to and stay within a specified set of legal states within bounded time regardless of its initial state. A self-stabilizing application therefore has the potential of recovering from the effects of arbitrary transient fail-urea. However, to actually verify that an application self-stabilizes can be quite tedious with current proof methodologies and is non-trivial. The self-stabilizing property of distributed algorithms exhibits interesting analogies to stabilizing feedback systems used in various engineering domains. In this paper we would like to show that techniques from control theory, namely Ljapunov's "Second Method," can be used to more easily verify the self-stabilization property of distributed algorithms.