2015
DOI: 10.1109/tdsc.2014.2315191
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On the Hardness of Adding Nonmasking Fault Tolerance

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Cited by 8 publications
(6 citation statements)
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“…Weak (respectively, strong) fairness policy ensures that any action that is continuously (respectively, infinitely often) enabled, will be executed infinitely often. We have shown [27] that synthesizing self-stabilization under weak fairness or no fairness assumptions is an NP-hard problem, whereas it is polynomially solvable under strong fairness [19] (because a strongly fair scheduler ensures recovery from lovelocks). In this paper, we make no assumption on fairness.…”
Section: Basic Conceptsmentioning
confidence: 99%
“…Weak (respectively, strong) fairness policy ensures that any action that is continuously (respectively, infinitely often) enabled, will be executed infinitely often. We have shown [27] that synthesizing self-stabilization under weak fairness or no fairness assumptions is an NP-hard problem, whereas it is polynomially solvable under strong fairness [19] (because a strongly fair scheduler ensures recovery from lovelocks). In this paper, we make no assumption on fairness.…”
Section: Basic Conceptsmentioning
confidence: 99%
“…For example, the design of parameterized self-stabilizing protocols algorithmically is known to be an open problem. Moreover, the problem of adding convergence to finite state automata is NP-hard (in the size of state space) [12,13,14]. Most existing techniques for the design of self-stabilization rely on a 'manual design and after-the-fact verification' methods which are limited to specific heuristics.…”
Section: List Of Tablesmentioning
confidence: 99%
“…Most existing techniques for the design of self-stabilization rely on a 'manual design and after-the-fact verification' methods which are limited to specific heuristics. Automatic finite-state synthesizers do exist [13,15,16,17] but they are efficient only in small scopes given the complexity of adding convergence problem (i.e., small finite number of processes) [15,16]. This dissertation includes two parts.…”
Section: List Of Tablesmentioning
confidence: 99%
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