Optimal Identification of Multiple Diffusion Sources in Complex Networks with Partial Observations

  • Xiang Li
  • Xiaojie Wang
  • Chengli ZhaoEmail author
  • Xue Zhang
  • Dongyun Yi
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1074)


Source localization is a typical inverse problem in complex networks, which is widely used in disease outbreak, rumor propagation and pollutants spread. In this paper, we propose that, based on network topology and the times at which the diffusion reached partial nodes, it is easy to identify the source. The results show that in six different networks, although the number of observers is small, the precision of source localization can be high. Precision increases with network size increasing and source number decreasing. Furthermore, our method makes the sources localization precision very robust, not only with the condition of three different given observers selection strategies, but with three various intensity noise on the diffusion path.


Multiple sources localization Precision Robust 



This work is partially supported by the National Key R&D Program of China (Grant No. 2017YCF1200301), the Postgraduate Innovation Fund of Hunan Province (Grant No. CX2015B010), and the Postgraduate Innovation Fund of the National University of Defense Technology (Grant No. B150203).


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Xiang Li
    • 1
  • Xiaojie Wang
    • 1
  • Chengli Zhao
    • 1
    Email author
  • Xue Zhang
    • 1
  • Dongyun Yi
    • 1
    • 2
  1. 1.College of Liberal Arts and SciencesNational University of Defense TechnologyChangshaChina
  2. 2.State Key Laboratory of High Performance ComputingNational University of Defense TechnologyChangshaChina

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