Local area network analysis using end-to-end delay tomography

Authors:
Earl Lawrence;George Michailidis;Vijay N. Nair
Affiliations:
Los Alamos Laboratory, Los Anamos NM;University of Michigan, Ann Arbor MI;University of Michigan, Ann Arbor MI
Venue:
ACM SIGMETRICS Performance Evaluation Review - Special issue on the First ACM SIGMETRICS Workshop on Large Scale Network Inference (LSNI 2005)
Year:
2005

Citing 5
Cited 0

Multicast-based inference of network-internal delay distributions

IEEE/ACM Transactions on Networking (TON)
An information-theoretic approach to traffic matrix estimation

Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Maximum pseudo likelihood estimation in network tomography

IEEE Transactions on Signal Processing
Network delay tomography

IEEE Transactions on Signal Processing
Multicast-based inference of network-internal loss characteristics

IEEE Transactions on Information Theory

Quantified Score

Hi-index	0.00

Visualization

Abstract

There has been considerable interest over the last few years in collecting and analyzing internet traffic data in order to estimate quality of service parameters such as packet loss rates and delay distributions. In this paper, we focus on fast and efficient estimation methods for network link delay distributions based on end-to-end measurements obtained by probing the underlying. We introduce a rigorous statistical framework for designing the necessary probing experiments and examine the properties of the proposed estimators. The proposed framework and the resulting methodology are validated using data collected on the University of North Carolina (UNC) local area network.