{"title":"时间可达性支配集:时间图中的传染","authors":"David C. Kutner , Laura Larios-Jones","doi":"10.1016/j.jcss.2025.103701","DOIUrl":null,"url":null,"abstract":"<div><div>Given a population with dynamic pairwise connections, we ask if the entire population could be (indirectly) infected by a small group of <em>k</em> initially infected individuals. We formalise this problem as the <span>Temporal Reachability Dominating Set</span> (<span>TaRDiS</span>) problem on temporal graphs. We provide positive and negative parameterized complexity results in four different parameters: the number <em>k</em> of initially infected, the lifetime <em>τ</em> of the graph, the number of locally earliest edges in the graph, and the treewidth of the footprint graph <span><math><msub><mrow><mi>G</mi></mrow><mrow><mo>↓</mo></mrow></msub></math></span>. We additionally introduce and study the <span>MaxMinTaRDiS</span> problem, where the aim is to schedule connections between individuals so that at least <em>k</em> individuals must be infected for the entire population to become fully infected. We classify three variants of the problem: Strict, Nonstrict, and Happy. We show these to be coNP-complete, NP-hard, and <span><math><msubsup><mrow><mi>Σ</mi></mrow><mrow><mn>2</mn></mrow><mrow><mi>P</mi></mrow></msubsup></math></span>-complete, respectively. Interestingly, we obtain hardness of the Nonstrict variant by showing that a natural restriction is exactly the well-studied <span>Distance-3 Independent Set</span> problem on static graphs.</div></div>","PeriodicalId":50224,"journal":{"name":"Journal of Computer and System Sciences","volume":"155 ","pages":"Article 103701"},"PeriodicalIF":0.9000,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Temporal Reachability Dominating Sets: Contagion in temporal graphs\",\"authors\":\"David C. Kutner , Laura Larios-Jones\",\"doi\":\"10.1016/j.jcss.2025.103701\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Given a population with dynamic pairwise connections, we ask if the entire population could be (indirectly) infected by a small group of <em>k</em> initially infected individuals. We formalise this problem as the <span>Temporal Reachability Dominating Set</span> (<span>TaRDiS</span>) problem on temporal graphs. We provide positive and negative parameterized complexity results in four different parameters: the number <em>k</em> of initially infected, the lifetime <em>τ</em> of the graph, the number of locally earliest edges in the graph, and the treewidth of the footprint graph <span><math><msub><mrow><mi>G</mi></mrow><mrow><mo>↓</mo></mrow></msub></math></span>. We additionally introduce and study the <span>MaxMinTaRDiS</span> problem, where the aim is to schedule connections between individuals so that at least <em>k</em> individuals must be infected for the entire population to become fully infected. We classify three variants of the problem: Strict, Nonstrict, and Happy. We show these to be coNP-complete, NP-hard, and <span><math><msubsup><mrow><mi>Σ</mi></mrow><mrow><mn>2</mn></mrow><mrow><mi>P</mi></mrow></msubsup></math></span>-complete, respectively. Interestingly, we obtain hardness of the Nonstrict variant by showing that a natural restriction is exactly the well-studied <span>Distance-3 Independent Set</span> problem on static graphs.</div></div>\",\"PeriodicalId\":50224,\"journal\":{\"name\":\"Journal of Computer and System Sciences\",\"volume\":\"155 \",\"pages\":\"Article 103701\"},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2025-08-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computer and System Sciences\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0022000025000832\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computer and System Sciences","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0022000025000832","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
Temporal Reachability Dominating Sets: Contagion in temporal graphs
Given a population with dynamic pairwise connections, we ask if the entire population could be (indirectly) infected by a small group of k initially infected individuals. We formalise this problem as the Temporal Reachability Dominating Set (TaRDiS) problem on temporal graphs. We provide positive and negative parameterized complexity results in four different parameters: the number k of initially infected, the lifetime τ of the graph, the number of locally earliest edges in the graph, and the treewidth of the footprint graph . We additionally introduce and study the MaxMinTaRDiS problem, where the aim is to schedule connections between individuals so that at least k individuals must be infected for the entire population to become fully infected. We classify three variants of the problem: Strict, Nonstrict, and Happy. We show these to be coNP-complete, NP-hard, and -complete, respectively. Interestingly, we obtain hardness of the Nonstrict variant by showing that a natural restriction is exactly the well-studied Distance-3 Independent Set problem on static graphs.
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.