  We study the problem of link and node delay estimation in undirected networks
when at most k out of n links or nodes in the network are congested. Our
approach relies on end-to-end measurements of path delays across pre-specified
paths in the network. We present a class of algorithms that we call FRANTIC.
The FRANTIC algorithms are motivated by compressive sensing; however, unlike
traditional compressive sensing, the measurement design here is constrained by
the network topology and the matrix entries are constrained to be positive
integers. A key component of our design is a new compressive sensing algorithm
SHO-FA-INT that is related to the prior SHO-FA algorithm for compressive
sensing, but unlike SHO-FA, the matrix entries here are drawn from the set of
integers {0, 1, ..., M}. We show that O(k log n /log M) measurements suffice
both for SHO-FA-INT and FRANTIC. Further, we show that the computational
complexity of decoding is also O(k log n/log M) for each of these algorithms.
Finally, we look at efficient constructions of the measurement operations
through Steiner Trees.
