  Source localization, the act of finding the originator of a disease or rumor
in a network, has become an important problem in sociology and epidemiology.
The localization is done using the infection state and time of infection of a
few designated sensor nodes; however, maintaining sensors can be very costly in
practice.
  We propose the first online approach to source localization: We deploy a
priori only a small number of sensors (which reveal if they are reached by an
infection) and then iteratively choose the best location to place new sensors
in order to localize the source. This approach allows for source localization
with a very small number of sensors; moreover, the source can be found while
the epidemic is still ongoing. Our method applies to a general network topology
and performs well even with random transmission delays.
