  One of the purposes of network tomography is to infer the status of
parameters (e.g., delay) for the links inside a network through end-to-end
probing between (external) boundary nodes along predetermined routes. In this
work, we apply concepts from compressed sensing and expander graphs to the
delay estimation problem. We first show that a relative majority of network
topologies are not expanders for existing expansion criteria. Motivated by this
challenge, we then relax such criteria, enabling us to acquire simulation
evidence that link delays can be estimated for 30% more networks. That is, our
relaxation expands the list of identifiable networks with bounded estimation
error by 30%. We conduct a simulation performance analysis of delay estimation
and congestion detection on the basis of l1 minimization, demonstrating that
accurate estimation is feasible for an increasing proportion of networks.
