直径约束可靠性的因式分解理论

E. Canale, P. Romero, G. Rubino
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引用次数: 4

摘要

在经典的网络可靠性中,所研究的系统是一个具有完美节点和不完美链路的网络,它们随机独立地发生故障。该领域的典型问题是找到结果随机图连接的概率(或者更一般地说,给定的节点子集K属于相同的连接组件),称为可靠性。虽然(也因为)精确的可靠性计算属于NP-Hard问题,但鉴于模型的重要性,文献提供了许多方法来实现这一目的。本文讨论直径约束可靠性,这是2001年定义的一个类似度量,灵感来自电信中的延迟敏感应用,其中终端需要以d跳或更少的速度连接,对于给定的正整数d称为直径。因式分解理论是经典网络可靠性研究的基本工具之一,目前已是一个成熟的研究领域。然而,将其扩展到直径受限的环境中,至少需要识别不相关的链接,这是一个悬而未决的问题。在本文中,在最基本的、到目前为止最常用的情况下,在源端情况下,有效地确定了不相关的链路,其中|K| = 2,从而为直径约束可靠性的因数分解理论提供了第一步。我们还讨论了一些特殊图的度量值,并提出了一个具体的因式分解算法。论文最后讨论了未来工作的趋势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Factorization theory in diameter constrained reliability
In classical network reliability, the system under study is a network with perfect nodes and imperfect links that fail randomly and independently. The typical problem in the area is to find the probability that the resulting random graph is connected( or more generally, that a given subset K of nodes belong to the same connected component), called reliability. Although (and because) the exact reliability computation belongs to the class of NP-Hard problems, the literature offers many methods for this purpose, given the importance of the models. This paper deals with diameter-constrained reliability, a similar metric defined in 2001, inspired by delay-sensitive applications in telecommunications, where terminals are required to be connected by d hops or less, for a given positive integer d called diameter. Factorization theory is one of the fundamental tools of classical network reliability, and today it is a mature area. However, its extension to the diameter-constrained context requires at least the recognition of irrelevant links, which is an open problem. In this paper, irrelevant links are efficiently determined in the most basic and, by far, used case, the source-terminal one, where |K| = 2, thus providing a first step towards a Factorization theory in diameter constrained reliability. We also discuss the metric value in some special graphs, and we propose a specific Factoring algorithm. The paper is closed with a discussion of trends for future work.
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