Enright, J. and Meeks, K. and Mertzios, G.B. and Zamaraev, V. (2019) 'Deleting edges to restrict the size of an epidemic in temporal networks.', in 44th International Symposium on Mathematical Foundations of Computer Science. Saarbrücken/Wadern: Schloss Dagstuhl, 57:1-57:15. LIPIcs (Leibniz International Proceedings in Informatics). (138).
Spreading processes on graphs are a natural model for a wide variety of real-world phenomena, including information or behaviour spread over social networks, biological diseases spreading over contact or trade networks, and the potential flow of goods over logistical infrastructure. Often, the networks over which these processes spread are dynamic in nature, and can be modeled with graphs whose structure is subject to discrete changes over time, i.e. with temporal graphs. Here, we consider temporal graphs in which edges are available at specified timesteps, and study the problem of deleting edges from a given temporal graph in order to reduce the number of vertices (temporally) reachable from a given starting point. This could be used to control the spread of a disease, rumour, etc. in a temporal graph. In particular, our aim is to find a temporal subgraph in which a process starting at any single vertex can be transferred to only a limited number of other vertices using a temporally-feasible path (i.e. a path, along which the times of the edge availabilities increase). We introduce a natural deletion problem for temporal graphs and we provide positive and negative results on its computational complexity, both in the traditional and the parameterised sense (subject to various natural parameters), as well as addressing the approximability of this problem.
|Item Type:||Book chapter|
|Full text:||Publisher-imposed embargo |
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|Publisher Web site:||https://doi.org/10.4230/LIPIcs.MFCS.2019.57|
|Publisher statement:||© Jessica Enright, Kitty Meeks, George B. Mertzios, and Viktor Zamaraev; licensed under Creative Commons License CC-BY.|
|Date accepted:||11 June 2019|
|Date deposited:||23 July 2019|
|Date of first online publication:||23 August 2019|
|Date first made open access:||08 November 2019|
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