Temporal reachability minimization: Delaying vs. deleting

IF 1.1 3区 计算机科学 Q1 BUSINESS, FINANCE
Hendrik Molter , Malte Renken , Philipp Zschoche
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引用次数: 0

Abstract

We study spreading processes in temporal graphs, that is, graphs whose connections change over time. More precisely, we investigate how such a spreading process, emerging from a given set of sources, can be contained to a small part of the graph. We consider two ways of modifying the graph, which are (1) deleting and (2) delaying connections. We show a close relationship between the two associated problems. It is known that both problems are W[1]-hard when parameterized by the number of modifications. We consider the number of vertices to which the spread is contained as a parameter. Surprisingly, we prove W[1]-hardness for the deletion variant but fixed-parameter tractability for the delaying variant. Furthermore, we give a polynomial time algorithm for both problem variants when the graph has a tree structure and show how to generalize this result to an FPT-algorithm for the so-called timed feedback vertex number as a parameter.

时间可达性最小化:延迟与删除
我们研究的是时间图(即其连接随时间变化的图)中的传播过程。更准确地说,我们研究的是如何将这种从给定源集合中产生的传播过程控制在图的一小部分内。我们考虑了两种修改图的方法,即 (1) 删除和 (2) 延迟连接。我们展示了这两个相关问题之间的密切关系。众所周知,以修改次数为参数时,这两个问题都很难解决。我们将传播所包含的顶点数视为参数。令人惊讶的是,我们证明了删除变式的 W[1]-hardness 性,而延迟变式的固定参数可操作性。此外,我们还给出了当图形具有树形结构时这两个问题变体的多项式时间算法,并展示了如何将这一结果推广到以所谓的定时反馈顶点数为参数的 FPT 算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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