The DOI matches its Crossref record; 69 of the 69 references it cites were found in a registry or an index.
Measurements and analysis of end-to-end Internet dynamics
Open accessAbstract
Accurately characterizing end-to-end Internet dynamics - the performance that a user actually obtains from the lengthy series of network links that comprise a path through the Internet - is exceptionally difficult, due to the network`s immense heterogeneity. At the heart of this work is a `measurement framework` in which a number of sites around the Internet host a specialized measurement service. By coordinating `probes` between pairs of these sites one can measure end-to-end behavior along O(N2) paths for a framework consisting of N sites. Consequently, one obtains a superlinear scaling that allows measuring a rich cross-section of Internet behavior without requiring huge numbers of observation points. 37 sites participated in this study, allowing the author to measure more than 1,000 distinct Internet paths. The first part of this work looks at the behavior of end-to-end routing: the series of routers over which a connection`s packets travel. Based on 40,000 measurements made using this framework, the author analyzes: routing `pathologies` such as loops, outages, and flutter; the stability of routes over time; and the symmetry of routing along the two directions of an end-to-end path. The author finds that pathologies increased significantly over the course of 1995 and that Internet paths are heavily dominated by a single route. The second part of this work studies end-to-end Internet packet dynamics. The author analyzes 20,000 TCP transfers of 100 Kbyte each to investigate the performance of both the TCP endpoints and the Internet paths. The measurements used for this part of the study are much richer than those for the first part, but require a great degree of attention to issues of calibration, which are addressed by applying self-consistency checks to the measurements whenever possible. The author finds that packet filters are capable of a wide range of measurement errors, some of which, if undetected, can significantly taint subsequent analysis.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Savitzky-Golay Smoothing Filters
Press, W. H., & Teukolsky, S. A. (1990) · Computers in Physics · doi:10.1063/1.4822961 · Cited by 11,670
Random early detection gateways for congestion avoidance
Floyd, S., & Jacobson, V. (1993) · IEEE/ACM Transactions on Networking · doi:10.1109/90.251892 · Cited by 6,290
Congestion avoidance and control
Jacobson, V. (1995) · ACM SIGCOMM Computer Communication Review · doi:10.1145/205447.205462 · Cited by 5,301
On the self-similar nature of Ethernet traffic (extended version)
Leland, W. E., Taqqu, M. S., Willinger, W., & Wilson, D. V. (1994) · IEEE/ACM Transactions on Networking · doi:10.1109/90.282603 · Cited by 5,233
Ross, S. M. (1982) · Cited by 3,812
Wide area traffic: the failure of Poisson modeling
Paxson, V., & Floyd, S. (1995) · IEEE/ACM Transactions on Networking · doi:10.1109/90.392383 · Cited by 3,708
Self-citationIntegrated Services in the Internet Architecture: an Overview
Braden, R., Clark, D., & Shenker, S. (1994) · doi:10.17487/rfc1633 · Cited by 3,145
Mathematical Statistics and Data Analysis
Rabinowitz, L. (1989) · Technometrics · doi:10.1080/00401706.1989.10488573 · Cited by 3,116
(2011) · SpringerReference · doi:10.1007/springerreference_27387 · Cited by 3,053
The MD5 Message-Digest Algorithm
Rivest (1992) · Medical Entomology and Zoology · Cited by 2,853
Cited by
Wide-area Internet traffic patterns and characteristics
Thompson, K., Miller, G. J., & Wilder, R. (1997) · IEEE Network · doi:10.1109/65.642356 · Cited by 1,074
End-to-end Internet packet dynamics
Paxson, V. (1999) · IEEE/ACM Transactions on Networking · doi:10.1109/90.779192 · Cited by 908
Self-citationA signal analysis of network traffic anomalies
Barford, P., Kline, J., Plonka, D., & Ron, A. (2002) · Proceedings of the second ACM SIGCOMM Workshop on Internet measurment - IMW '02 · doi:10.1145/637201.637210 · Cited by 787
End-to-end routing behavior in the Internet
Paxson, V. (1997) · IEEE/ACM Transactions on Networking · doi:10.1109/90.649563 · Cited by 698
Self-citationThe end-to-end effects of Internet path selection
Savage, S., Collins, A., Hoffman, E., Snell, J., & Anderson, T. (1999) · Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication · doi:10.1145/316188.316233 · Cited by 473
On estimating end-to-end network path properties
Allman, M., & Paxson, V. (1999) · Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication · doi:10.1145/316188.316230 · Cited by 344
Self-citationA Machine Learning Approach to TCP Throughput Prediction
Mirza, M., Sommers, J., Barford, P., & Zhu, X. (2010) · IEEE/ACM Transactions on Networking · doi:10.1109/tnet.2009.2037812 · Cited by 132
Bayesian packet loss detection for TCP
I'onseca, N., & Crovella, M. (2005) · Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies. · doi:10.1109/infcom.2005.1498462 · Cited by 27
Metadata
- Authors
- Paxson, V.
- Published
- 1997-04-01
- OpenAlex
- W2156725431
- Cited by
- 572
- References
- 69
- Type
- report
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.