Name
Abstract | ||
|---|---|---|
Network immunization has been widely adopted for restraining epidemic spreading. Majority of the existing results on identifying immunization targets and the measurements of their effectiveness are based purely on network topology. However the topological heuristic strategies neglect important features of the spreading dynamics and consequently may cannot yield reliable results. In this paper, we present a novel network immunization strategy based on explosive percolation and message passing, which considers both the network topology and epidemic dynamic. We compare its performance with the greedy strategy, topological heuristic strategy and random strategy. The results demonstrate the efficiency of our method on a variety of real-world examples. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.amc.2019.124728 | Applied Mathematics and Computation |
Keywords | Field | DocType |
Network immunization,Spreading,Message passing,Explosive percolation,Vertex cover | Mathematical optimization,Heuristic,Explosive material,Network topology,Percolation,Mathematics,Message passing | Journal |
Volume | ISSN | Citations |
366 | 0096-3003 | 1 |
PageRank | References | Authors |
0.36 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shudong Li | 1 | 47 | 12.98 |
| Dawei Zhao | 2 | 193 | 20.38 |
| Xiaobo Wu | 3 | 1 | 0.36 |
| Zhi-Hong Tian | 4 | 312 | 52.75 |
| Aiping Li | 5 | 1 | 0.70 |
| Zhen Wang | 6 | 1060 | 85.86 |