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
Network tomography on general topologies
SIGMETRICS '02 Proceedings of the 2002 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Network topology generators: degree-based vs. structural
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
Topology Discovery by Active Probing
SAINT-W '02 Proceedings of the 2002 Symposium on Applications and the Internet (SAINT) Workshops
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
| Hi-index | 0.00 |
Tomographic techniques allow the reconstruction of network topologies with no need for cooperation from internal routers. However, most of such mechanisms adopt a method of node clustering producing trees that reveal only a partial structure of the network. Therefore, we have proposed a novel approach to topology discovery based on packet sandwich probes and decision theory allowing to retrieve a complete picture of the network, which includes the detection of all the internal nodes along with the values of capacities of the interconnecting links. Such an approach, as well as all the standard techniques of topology discovery, reconstructs the spanning tree of the probe sender only. Hence, in this paper a specific technique is presented for merging the spanning trees associated to all different roots, in order to provide a complete representation of the network. Such a method does not require further probing traffic and is specifically designed to merge topology reconstructions where all the nodes of the network (not only the branching nodes) are revealed, along with link capacities. Our algorithm performs quite well on a wide set of both synthetic and realistic topologies, and in many cases provides a picture of the network which is exactly equivalent to the original one.