We study the problem of identifying multiple rumor or infection sources in a network under the susceptible-infected (SI) model. We do not assume that the sources start infection spreading at the same time. We introduce the notion of a quasi-regular tree as the basic model, and an abstract estimator, which includes several of the single source estimators developed in the literature. We develop a general two source joint estimation algorithm based on any abstract estimator, and show that it converges to a local optimum of the estimation function if the underlying network is a quasi-regular tree. We further extend our algorithm to more than two sources, and heuristically to general graphs.
['Feng Ji', 'Wee Peng Tay']
Identifying rumor sources with different start times