Multicast-based inference of network-internal delay distributions
IEEE/ACM Transactions on Networking (TON)
Optimal Design of Experiments (Classics in Applied Mathematics) (Classics in Applied Mathematics, 50)
Measurement based analysis, modeling, and synthesis of the internet delay space
Proceedings of the 6th ACM SIGCOMM conference on Internet measurement
Network loss tomography using striped unicast probes
IEEE/ACM Transactions on Networking (TON)
Understanding network delay changes caused by routing events
Proceedings of the 2007 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Multicast inference of temporal loss characteristics
Performance Evaluation
Multicast-based inference of network-internal loss characteristics
IEEE Transactions on Information Theory
Multicast topology inference from measured end-to-end loss
IEEE Transactions on Information Theory
Toward a scalable and collaborative network monitoring overlay
TMA'11 Proceedings of the Third international conference on Traffic monitoring and analysis
A cooperative network monitoring overlay
NEW2AN'11/ruSMART'11 Proceedings of the 11th international conference and 4th international conference on Smart spaces and next generation wired/wireless networking
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Network tomography has been proposed to ascertain internal network performances from end-to-end measurements. In this work, we present priority probing, an optimal probing scheme for unicast network delay tomography that is proven to provide the most accurate estimation. We first demonstrate that the Fisher information matrix in unicast network delay tomography can be decomposed into an additive form where each term can be obtained numerically. This establishes the space over which we can design the optimal probing scheme. Then, we formulate the optimal probing problem into a semidefinite programming (SDP) problem. High computation complexity constrains the SDP solution to only small scale scenarios. In response, we propose a greedy algorithm that approximates the optimal solution. Evaluations through simulation demonstrate that priority probing effectively increases estimation accuracy with a fixed number of probes.