Locating the propagation source on complex networks with Propagation Centrality algorithm

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摘要

Propagation source location is an important problem which can help authorities developing control strategies on complex networks. In this paper, we study this problem by assuming that there is a single propagation source and the spreading process on networks follows the Susceptible-Infected (SI) model. We define a Rationality Observation Value (ROV) on infected tree that has a fixed root and propose the corresponding measuring method. Using ROV, we construct a source estimator for tree graph and generalize it to arbitrary graph. Based on the generalized estimator, a novel Propagation Centrality (PC) algorithm is proposed, which could locate the propagation source on arbitrary graph with complexity O(N3). With PC algorithm, source location is converted into finding out a Breadth-First-Search (BFS) spanning tree with the maximal ROV from infected graph. We perform extensive simulations on a series of synthetic and real networks, the results show that PC performs better than other 5 existing methods. More importantly, the results also show that PC performs stable on the infected graph with sparse observation phenomenon.

论文关键词:Complex networks,Propagation source location,Susceptible-Infected (SI) model,Rationality Observation Value (ROV),Propagation Centrality (PC) algorithm,Sparse observation

论文评审过程:Received 23 June 2015, Revised 17 February 2016, Accepted 19 February 2016, Available online 3 March 2016, Version of Record 2 April 2016.

论文官网地址:https://doi.org/10.1016/j.knosys.2016.02.013