An exercise in proving self-stabilization with a variant function
Information Processing Letters
Information Processing Letters
Fault tolerance in distributed systems
Fault tolerance in distributed systems
Memory requirements for silent stabilization
PODC '96 Proceedings of the fifteenth annual ACM symposium on Principles of distributed computing
Self-stabilization
Guarded commands, nondeterminacy and formal derivation of programs
Communications of the ACM
Exploitation of Ljapunov Theory for Verifying Self-Stabilizing Algorithms
DISC '00 Proceedings of the 14th International Conference on Distributed Computing
An exercise in proving convergence through transfer functions
ICDCS '99 Workshop on Self-stabilizing Systems
Towards automatic convergence verification of self-stabilizing algorithms
SSS'05 Proceedings of the 7th international conference on Self-Stabilizing Systems
Stabilization in dynamic systems with varying equilibrium
SSS'07 Proceedings of the 9h international conference on Stabilization, safety, and security of distributed systems
Hi-index | 0.00 |
Self-stabilization is a novel method for achieving fault tolerance in distributed applications. A self-stabilizing algorithm will reach a legal set of states, regardless of the starting state or states adopted due to the effects of transient faults, in finite time. However, proving self-stabilization is a difficult task. In this paper, we present a method for showing self-stabilization of a class of non-silent distributed algorithms, namely orbitally self-stabilizing algorithms. An algorithm of this class is modeled as a hybrid feedback control system. We then employ the control theoretic methods of Poincaré maps and Lyapunov functions to show convergence to an orbit cycle.