A robust information source estimator with sparse observations

Kai Zhu, Lei Ying

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Scopus citations

Abstract

In this paper, we consider the problem of locating the information source with sparse observations. We assume that a piece of information spreads in a network following a heterogeneous susceptible-infected-recovered (SIR) model, where a node is said to be infected when it receives the information and recovered when it removes or hides the information. We further assume that a small subset of infected nodes are reported, from which we need to find the source of the information. We adopt the sample path based estimator developed in [1], and prove that on infinite trees, the sample path based estimator is a Jordan infection center with respect to the set of observed infected nodes. In other words, the sample path based estimator minimizes the maximum distance to observed infected nodes. We further prove that the distance between the estimator and the actual source is upper bounded by a constant independent of the number of infected nodes with a high probability on infinite trees. Our simulations on tree networks and real world networks show that the sample path based estimator is closer to the actual source than several other algorithms.

Original languageEnglish (US)
Title of host publicationIEEE INFOCOM 2014 - IEEE Conference on Computer Communications
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2211-2219
Number of pages9
ISBN (Print)9781479933600
DOIs
StatePublished - Jan 1 2014
Event33rd IEEE Conference on Computer Communications, IEEE INFOCOM 2014 - Toronto, ON, Canada
Duration: Apr 27 2014May 2 2014

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X

Other

Other33rd IEEE Conference on Computer Communications, IEEE INFOCOM 2014
CountryCanada
CityToronto, ON
Period4/27/145/2/14

ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering

Cite this

Zhu, K., & Ying, L. (2014). A robust information source estimator with sparse observations. In IEEE INFOCOM 2014 - IEEE Conference on Computer Communications (pp. 2211-2219). [6848164] (Proceedings - IEEE INFOCOM). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/INFOCOM.2014.6848164