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Passive estimation of TCP round-trip times

Authors:

Constantinos DovrolisAuthors Info & Claims

ACM SIGCOMM Computer Communication Review, Volume 32, Issue 3

Pages 75 - 88

https://doi.org/10.1145/571697.571725

Published: 01 July 2002 Publication History

Abstract

We propose and evaluate a passive measurement methodology that estimates the distribution of Round-Trip Times (RTTs) for the TCP connections that flow through a network link. Such an RTT distribution is important in buffer provisioning, configuration of active queue management, and detection of congestion unresponsive traffic. The proposed methodology is based on two techniques. The first technique is applicable to TCP caller-to-callee flows, and it is based on the 3-way handshake messages. The second technique is applicable to callee-to-caller flows, when the callee transfers a number of MSS segments to the caller, and it is based on the slow-start phase of TCP. The complete estimation algorithm reports an RTT for 55-85% of the TCP workload, in terms of bytes, in the traces that we examined. Verification experiments show that about 90% of the passive measurements are within 10% or 5ms, whichever is larger, of the RTT that ping would measure. Also, measurements on several NLANR traces show that the two estimation techniques agree within 25ms for 70-80% of the processed TCP connections. We also apply the estimation methodology on a number of NLANR traces and examine the variability of the measured RTT distributions in both short and long timescales.

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Passive estimation of TCP round-trip times

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Published In

cover image ACM SIGCOMM Computer Communication Review

ACM SIGCOMM Computer Communication Review Volume 32, Issue 3

July 2002

79 pages

ISSN:0146-4833

DOI:10.1145/571697

Issue’s Table of Contents

Copyright © 2002 Authors.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 July 2002

Published in SIGCOMM-CCR Volume 32, Issue 3

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https://doi.org/10.1109/TCCN.2023.3329024
Chen BIvanov NWang GYan Q(2023)DynamicFL: Balancing Communication Dynamics and Client Manipulation for Federated Learning2023 20th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)10.1109/SECON58729.2023.10287430(312-320)Online publication date: 11-Sep-2023
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https://doi.org/10.1109/ISSC59246.2023.10162121
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