Robust multi-source network tomography using selective probes

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Robust multi-source network tomography using selective probes
—Knowledge of a network’s topology and internal characteristics such as delay times or losses is crucial to maintain seamless operation of network services. Network tomography is a useful approach to infer such knowledge from end-to-end measurements between nodes at the periphery of the network, as it does not require cooperation of routers and other internal nodes. Most current tomography algorithms are single-source methods, which use multicast probes or synchronized unicast packet trains to measure covariances between destinations from a single vantage point and recover a tree topology from these measurements. Multi-source tomography, on the other hand, uses pairwise hop counts or latencies and consequently overcomes the difficulties associated with obtaining measurements for singlesource methods. However, topology recovery is complicated by the fact that the paths along which measurements are taken do not form a tree in the network. Motivated by recent work suggesting that the...
Akshay Krishnamurthy, Aarti Singh
Added 28 Sep 2012
Updated 28 Sep 2012
Type Journal
Year 2012
Authors Akshay Krishnamurthy, Aarti Singh
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