Network Tomography via Compressed Sensing

Abstract

In network tomography, we seek to infer link parameters inside a network (such as link delays) by sending end-to-end probes between (external) boundary nodes. The main challenge here is to estimate link-level attributes from end-to-end measurements. In this paper, based on the idea of combinatorial compressed sensing, we specify conditions on network routing matrix under which it is possible to estimate link delays from measurements of end-to-end delay. Moreover, we provide an upper-bound on the estimation error.