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Network topology inference from infection statistics

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  • Tomovski, Igor
  • Kocarev, Ljupčo

Abstract

We introduce a mathematical framework for identification of network topology, based on data collected from infectious SIS process occurring on a network. An exact expression for the weight of each network link (existing or not) as a function of infectious statistics, is obtained. An algorithm for proper implementation of the analyzed concept is suggested and the validity of the obtained result is confirmed by numerical simulations performed on a number of synthetic (computer generated) networks.

Suggested Citation

  • Tomovski, Igor & Kocarev, Ljupčo, 2015. "Network topology inference from infection statistics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 272-285.
    • Handle: RePEc:eee:phsmap:v:436:y:2015:i:c:p:272-285
    DOI: 10.1016/j.physa.2015.03.090
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    References listed on IDEAS

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    Cited by:

    1. Pandey, Pradumn Kumar & Badarla, Venkataramana, 2018. "Reconstruction of network topology using status-time-series data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 573-583.

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    Keywords

    Network topology; SIS process;

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