English

Parameterized Complexity of Immunization in the Threshold Model

Computational Complexity 2021-02-09 v1 Discrete Mathematics Data Structures and Algorithms Combinatorics

Abstract

We consider the problem of controlling the spread of harmful items in networks, such as the contagion proliferation of diseases or the diffusion of fake news. We assume the linear threshold model of diffusion where each node has a threshold that measures the node resistance to the contagion. We study the parameterized complexity of the problem: Given a network, a set of initially contaminated nodes, and two integers kk and \ell, is it possible to limit the diffusion to at most kk other nodes of the network by immunizing at most \ell nodes? We consider several parameters associated to the input, including: the bounds kk and \ell, the maximum node degree Δ\Delta, the treewidth, and the neighborhood diversity of the network. We first give W[1]W[1] or W[2]W[2]-hardness results for each of the considered parameters. Then we give fixed-parameter algorithms for some parameter combinations.

Keywords

Cite

@article{arxiv.2102.03537,
  title  = {Parameterized Complexity of Immunization in the Threshold Model},
  author = {Gennaro Cordasco and Luisa Gargano and Adele Anna Rescigno},
  journal= {arXiv preprint arXiv:2102.03537},
  year   = {2021}
}
R2 v1 2026-06-23T22:53:49.991Z