关于计算大时间(单边)连接成分

IF 1.1 3区 计算机科学 Q1 BUSINESS, FINANCE
Isnard Lopes Costa , Raul Lopes , Andrea Marino , Ana Silva
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引用次数: 0

摘要

这些图中的路径是相邻边的序列,其出现时间要么严格递增,要么非严格递增。连通部分和单边部分的经典概念可以自然地扩展到时间图。我们要解决时间图中的基本问题。(i) 由 τ、k 和 k+τ 参数决定大小为 k 的分量是否存在的复杂度是多少?答案取决于组件的定义以及图是有向图还是无向图。(ii) 检查顶点子集是否成对可达的最小运行时间是多少?存在二次方时间算法,但除非 SETH 失败,否则不太可能有更快的时间。(iii) 我们能否在多项式时间内验证顶点子集是否构成一个组件?这取决于时间分量的定义,是 NP -complete 的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On computing large temporal (unilateral) connected components

A temporal (directed) graph is one where edges are available only at specific times during its lifetime, τ. Paths in these graphs are sequences of adjacent edges whose appearing times are either strictly increasing or non-strictly increasing. Classical concepts of connected and unilateral components can be naturally extended to temporal graphs. We address fundamental questions in temporal graphs. (i) What is the complexity of deciding the existence of a component of size k, parameterized by τ, k, and k+τ? The answer depends on the component definition and whether the graph is directed or undirected. (ii) What is the minimum running time to check if a subset of vertices is pairwise reachable? A quadratic-time algorithm exists, but a faster time is unlikely unless SETH fails. (iii) Can we verify if a subset of vertices forms a component in polynomial time? This is NP -complete depending on the temporal component definition.

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来源期刊
Journal of Computer and System Sciences
Journal of Computer and System Sciences 工程技术-计算机:理论方法
CiteScore
3.70
自引率
0.00%
发文量
58
审稿时长
68 days
期刊介绍: The Journal of Computer and System Sciences publishes original research papers in computer science and related subjects in system science, with attention to the relevant mathematical theory. Applications-oriented papers may also be accepted and they are expected to contain deep analytic evaluation of the proposed solutions. Research areas include traditional subjects such as: • Theory of algorithms and computability • Formal languages • Automata theory Contemporary subjects such as: • Complexity theory • Algorithmic Complexity • Parallel & distributed computing • Computer networks • Neural networks • Computational learning theory • Database theory & practice • Computer modeling of complex systems • Security and Privacy.
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