Optimal Identification of Multiple Diffusion Sources in Complex Networks with Partial Observations
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.
KeywordsMultiple 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).
- 7.Nguyen, H.T. , et al.: Multiple infection sources identification with provable guarantees. In: The 25th ACM International. ACM (2016). https://doi.org/10.1145/2983323.2983817
- 11.Zhu, K., Chen, Z., Ying, L.: Catch’Em all: locating multiple diffusion sources in networks with partial observations (2016)Google Scholar
- 13.Hu, Z.L., Shen, Z., Cao, S.: Locating multiple diffusion sources in time varying networks from sparse observations. Sci. Rep. 8(1) (2018). https://doi.org/10.1038/s41598-018-20033-9