Time optimal self-stabilizing synchronization
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
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Self-stabilizing systems in spite of distributed control
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Self-stabilization with r-operators
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A Self-stabilizing Approximation for the Minimum Connected Dominating Set with Safe Convergence
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Robust self-stabilizing weight-based clustering algorithm
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A new self-stabilizing minimum spanning tree construction with loop-free property
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A self-stabilizing minimal dominating set algorithm with safe convergence
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SSS'10 Proceedings of the 12th international conference on Stabilization, safety, and security of distributed systems
Snap-stabilizing linear message forwarding
SSS'10 Proceedings of the 12th international conference on Stabilization, safety, and security of distributed systems
Robust self-stabilizing clustering algorithm
OPODIS'06 Proceedings of the 10th international conference on Principles of Distributed Systems
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ALGOSENSORS'06 Proceedings of the Second international conference on Algorithmic Aspects of Wireless Sensor Networks
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A distributed system is self-stabilizing if it returns to a legitimate state in a finite number of steps regardless of the initial state, and the system remains in a legitimate state until another fault occurs. A routing algorithm is loop-free if, a path being constructed between two processors p and q, any edges cost change induces a modification of the routing tables in such a way that at any time, there always exists a path from p to q. We present a self-stabilizing loop-free routing algorithm that is also route preserving. This last property means that, a tree being constructed, any message sent to the root is received in a bounded amount of time, even in the presence of continuous edge cost changes. Also, and unlike previous approaches, we do not require that a bound on the network diameter is known to the processors that perform the routing algorithm. We guarantee self-stabilization for many metrics (such as minimum distance, shortest path, best transmitter, depth first search metrics, etc.), by reusing previous results on r-operators.