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The contribution of this paper is threefold. First, we present the paradigm of snap-stabilization. A snap- stabilizing protocol guarantees that, starting from an arbitrary system configuration, the protocol always behaves according to its specification. So, a snap-stabilizing protocol is a time...
An alternator is an array of interacting processes that satisfy three conditions. First, if a process has an enabled action at some state, then no neighbor of that process has an enabled action at the same state. Second, along any concurrent execution, each action is executed infinitely often....
Self-stabilizing algorithms automatically recover from any occurrence of a transient fault. The global state following the transient fault is considered to be the initial state for subsequent execution. An adaptive self-stabilizing algorithm changes its behavior based on characteristics of the...
We present fault detectors for transient faults, (i.e., corruptions of the memory of the processors, but not of the code of the processors). We distinguish fault detectors for tasks (i.e., the problem to be solved) from failure detectors for implementations (i.e., the algorithm that solves the...
Self-stabilization is an elegant approach for designing a class of fault-tolerant distributed protocols. A self-stabilizing protocol is guaranteed to eventually converge to a legitimate state after a transient fault. However, even a minor transient fault can cause vast disruption in the system...
We present a randomized self-stabilizing leader election protocol and a randomized self-stabilizing token circulation protocol under an arbitrary scheduler on anonymous and unidirectional rings of any size. These protocols are space optimal. We also give a formal and complete proof of these...
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