Shape matching using edit-distance: an implementation
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
Maximum likelihood network topology identification from edge-based unicast measurements
SIGMETRICS '02 Proceedings of the 2002 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
BRITE: Universal Topology Generation from a User''s Perspective
BRITE: Universal Topology Generation from a User''s Perspective
Topology discovery in heterogeneous IP networks: the NetInventory system
IEEE/ACM Transactions on Networking (TON)
Network tomography from measured end-to-end delay covariance
IEEE/ACM Transactions on Networking (TON)
Likelihood based hierarchical clustering
IEEE Transactions on Signal Processing
Multicast topology inference from measured end-to-end loss
IEEE Transactions on Information Theory
An OSPF topology server: design and evaluation
IEEE Journal on Selected Areas in Communications
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Network Topology Discovery is crucial to a number of network management tasks. Traditional topology discovery techniques require internal nodes to take actions on measurement packets, which makes them unpractical in many cases. For these reasons, tomographic techniques have been introduced, which allow for the reconstruction of network topologies with no need for cooperation from internal routers. The usual approach to tomographic topology discovery is based on clustering nodes into tree structures according to soft similarity metrics. We recently proposed a novel technique based on decision theoretic considerations that help the topology reconstruction by limiting the set of hypotheses to a finite and well-defined set, thus determing hard metrics. In the scheme, probe traffic is sent to all couples of end-nodes and a metric is assigned to each measurement. In this paper, we extend the technique by ordering the topology reconstruction procedure according to metrics reliability defined in terms of their variances. The algorithms presented in the paper are validated through extensive simulations in several network scenarios. The results show that such a methodology allows to retrieve a complete picture of the network that includes the detection of all the internal nodes along with the values of capacities of the interconnecting links.