000227206 001__ 227206
000227206 005__ 20190317000656.0
000227206 0247_ $$2doi$$a10.1145/3038912.3052584
000227206 037__ $$aCONF
000227206 245__ $$aBack to the Source: an Online Approach for Sensor Placement and Source Localization
000227206 269__ $$a2017
000227206 260__ $$c2017
000227206 336__ $$aConference Papers
000227206 520__ $$aSource 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.
000227206 6531_ $$aepidemics
000227206 6531_ $$asource localization
000227206 6531_ $$asensor placement
000227206 700__ $$0247061$$g226024$$aSpinelli, Brunella Marta
000227206 700__ $$0248244$$g245193$$aCelis, Elisa
000227206 700__ $$aThiran, Patrick$$g103925$$0240373
000227206 7112_ $$a26th International World Wide Web Conference (WWW)
000227206 8564_ $$uhttps://infoscience.epfl.ch/record/227206/files/www17_camera.pdf$$zPublisher's version$$s1511941$$yPublisher's version
000227206 909C0 $$xU10431$$0252454$$pLCA3
000227206 909CO $$ooai:infoscience.tind.io:227206$$qGLOBAL_SET$$pconf$$pIC
000227206 917Z8 $$x226024
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000227206 917Z8 $$x226024
000227206 917Z8 $$x226024
000227206 937__ $$aEPFL-CONF-227206
000227206 973__ $$rREVIEWED$$sPUBLISHED$$aEPFL
000227206 980__ $$aCONF