Name
Abstract | ||
|---|---|---|
We survey some results on the localization of the source of diffusion in a network. There have been significant efforts in studying the dynamics of epidemic propagations on networks, and more particularly on the forward problem of epidemics: understanding the diffusion process and its dependence on the infecting and curing rates. We address here the inverse problem of inferring the original source of diffusion. If we could observe the entire diffusion process and collect the times at which nodes of the network get infected, identifying its source would be easy. Unfortunately, due to the costs of information collection and to overhead constraints, the data available for source localization is usually very sparse, first because the information that can provided by a node is limited, and second because the number of nodes in the network is often prohibitively large, and only some of them, which we call hereafter sensors, might be able or willing to provide any information about their state.
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Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3308897.3308921 | ACM SIGMETRICS Performance Evaluation Review |
Keywords | Field | DocType |
algorithms, epidemics, inverse problem, random networks | Diffusion process,Computer science,Source localization,Inverse problem,Distributed computing | Journal |
Volume | Issue | ISSN |
46 | 3 | 0163-5999 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Patrick Thiran | 1 | 2712 | 217.24 |