Network tomography from measured end-to-end delay covariance

End-to-end measurement is a common tool for network performance diagnosis, primarily because it can reflect user experience and typically requires minimal support from intervening network elements. However, pinpointing the site of performance degradation from end-to-end measurements is a challenging problem. We show how end-to-end delay measurements of multicast traffic can be used to infer the under-lying logical multicast tree and the packet delay variance on each of its links. The method does not depend on cooperation from intervening network elements; multicast probing is bandwidth efficient. We establish desirable statistical properties of the estimator, namely consistency and asymptotic normality. We evaluate the approach through simulations, and analyze its failure modes and their probabilities.