Variability in TCP round-trip times
Proceedings of the 3rd ACM SIGCOMM conference on Internet measurement
Convergence Technologies for 3G Networks: IP, UMTS,EGPRS and ATM
Convergence Technologies for 3G Networks: IP, UMTS,EGPRS and ATM
Large-Scale RTT Measurements from an Operational UMTS/GPRS Network
WICON '05 Proceedings of the First International Conference on Wireless Internet
A passive state-machine approach for accurate analysis of TCP out-of-sequence segments
ACM SIGCOMM Computer Communication Review
Diagnosis of capacity bottlenecks via passive monitoring in 3G networks: An empirical analysis
Computer Networks: The International Journal of Computer and Telecommunications Networking
Passive analysis of TCP anomalies
Computer Networks: The International Journal of Computer and Telecommunications Networking
Network-Wide Measurements of TCP RTT in 3G
TMA '09 Proceedings of the First International Workshop on Traffic Monitoring and Analysis
An evaluation of dynamic adaptive streaming over HTTP in vehicular environments
Proceedings of the 4th Workshop on Mobile Video
Proceedings of the 2012 ACM conference on Internet measurement conference
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In this work we discuss the use of passive measurements of TCP performance indicators in support of network operation and troubleshooting, presenting a case-study from a real 3G cellular network. From the analysis of TCP handshaking packets measured in the core network we infer Round-Trip-Times (RTT) on both the client and server sides separately for UMTS/HSPA and GPRS/EDGE sections. We also keep track of the relative share of packet pairs which did not lead to a valid RTT sample, e.g. due to loss and/or retransmission events, and use this metric as an additional performance signal. In a previous work we identified the risk of measurement bias due to early retransmission of TCP SYNACK packets by some popular servers. In order to mitigate this problem we introduce here a novel algorithm for dynamic classification and filtering of early retransmitters. We present a few illustrative cases of abrupt-change observed in the real network, based on which we derive some lessons learned about using such data for detecting anomalies in a real network. Thanks to such measurements we were able to discover a hidden congestion bottleneck in the network under study.