Detecting multiple information sources in networks under the SIR model

Zhen Chen, Kai Zhu, Lei Ying

Research output: Contribution to journalArticlepeer-review

39 Scopus citations


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 languageEnglish (US)
Article number7395374
Pages (from-to)17-31
Number of pages15
JournalIEEE Transactions on Network Science and Engineering
Issue number1
StatePublished - Jan 1 2016


  • Information source detection
  • Multiple information sources
  • Sample path approach

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Computer Networks and Communications


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