Abstract
In this paper, we study the problem of detecting multiple information sources in networks under the Susceptible-Infected- Recovered (SIR) model. First, assuming the number of information sources is known, we develop a sample-path-based algorithm, named clustering and localization, for trees. For g-regular trees, the estimators produced by the proposed algorithm are within a constant distance from the real sources with a high probability. We further present a heuristic algorithm for general networks and an algorithm for estimating the number of sources when the number of real sources is unknown.
Original language | English (US) |
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Article number | 7395374 |
Pages (from-to) | 17-31 |
Number of pages | 15 |
Journal | IEEE Transactions on Network Science and Engineering |
Volume | 3 |
Issue number | 1 |
DOIs | |
State | Published - Jan 1 2016 |
Keywords
- Information source detection
- Multiple information sources
- Sample path approach
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science Applications
- Computer Networks and Communications