Titlebook: Stabilization, Safety, and Security of Distributed Systems; 8th International Sy Ajoy K. Datta,Maria Gradinariu Conference proceedings 2006

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A 1-Strong Self-stabilizing Transformeronfinement means that a non faulty processor has the same behavior with or without the presence of faults elsewhere in the system (in other words faults are confined). k-linear time adaptivity means that after k or less faults hitting the system in a correct state, the recovery takes a number of rou

Infect

Optimal Message-Driven Implementation of Omega with Mute Processes receptions but not by the passage of time. Hutle and Widder (2005) have shown that there is no self-stabilizing implementation of the eventually strong failure detector, and thus the eventual leader oracle Ω in such models under certain assumptions. Under stronger assumptions it was shown that even

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Incremental Synthesis of Fault-Tolerant Real-Time Programs fault-tolerance, namely ., ., and ., based on safety and liveness properties satisfied in the presence of faults. More specifically, a nonmasking (respectively, failsafe, masking) program satisfies liveness (respectively, safety, both safety and liveness) in the presence of faults. For failsafe and

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receptors

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enormous

Self-protection for Distributed Component-Based Applications promising approach to this issue is to implement a self-protected system, similarly to a natural immune system which has the ability to detect the intrusion of foreign elements and react while it is still in progress..This paper describes an approach relying on component-based software engineering

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From Self- to Snap- Stabilizationallowing to snap-stabilize self-stabilizing wave protocols for arbitrary networks with a unique initiator. To that goal, we consider such a self-stabilizing protocol .. We then slightly update . to obtain a protocol . that can be automatically transformed, using a black box protocol, into a snap-sta