Finding the Right Tree: Topology Inference Despite Spatial Dependencies

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Journal Article
IEEE Transactions on Information Theory, 2017
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IEEE Network tomographic techniques have almost exclusively been built on a strong assumption of mutual independence of link processes. We introduce model classes for link loss processes with non-trivial spatial dependencies, for which the tree topology is nonetheless identifiable from leaf measurements using multicast probing. We show that these classes are large in a well defined sense, and we provide an algorithm, SLTD, capable of returning the correct topology with certainty in the limit of infinite data.
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