Locating the propagation source on complex networks with Propagation Centrality algorithm

Abstract

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.