Dummynet: a simple approach to the evaluation of network protocols
ACM SIGCOMM Computer Communication Review
End-to-end routing behavior in the Internet
IEEE/ACM Transactions on Networking (TON)
End-to-end internet packet dynamics
IEEE/ACM Transactions on Networking (TON)
Packet reordering is not pathological network behavior
IEEE/ACM Transactions on Networking (TON)
Passive estimation of TCP round-trip times
ACM SIGCOMM Computer Communication Review
Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment
Multicast-based inference of network-internal loss characteristics
IEEE Transactions on Information Theory
Packet-level traffic measurements from the Sprint IP backbone
IEEE Network: The Magazine of Global Internetworking
Bottleneck detection in UMTS via TCP passive monitoring: a real case
CoNEXT '05 Proceedings of the 2005 ACM conference on Emerging network experiment and technology
Passive analysis of TCP anomalies
Computer Networks: The International Journal of Computer and Telecommunications Networking
CoNEXT '08 Proceedings of the 2008 ACM CoNEXT Conference
Sorting Reordered Packets with Interrupt Coalescing
Computer Networks: The International Journal of Computer and Telecommunications Networking
Measuring IP and TCP behavior on edge nodes with Tstat
Computer Networks: The International Journal of Computer and Telecommunications Networking
Hot data centers vs. cool peers
HotPower'08 Proceedings of the 2008 conference on Power aware computing and systems
A self-adversarial approach to delay analysis under arbitrary scheduling
ISoLA'10 Proceedings of the 4th international conference on Leveraging applications of formal methods, verification, and validation - Volume Part I
Understanding the impact of the access technology: the case of web search services
TMA'11 Proceedings of the Third international conference on Traffic monitoring and analysis
Exposing invisible timing-based traffic watermarks with BACKLIT
Proceedings of the 27th Annual Computer Security Applications Conference
MALAWI: aggregated longitudinal analysis of the MAWI dataset
Proceedings of The ACM CoNEXT Student Workshop
Detecting and profiling TCP connections experiencing abnormal performance
TMA'12 Proceedings of the 4th international conference on Traffic Monitoring and Analysis
Implementing information-theoretically secure oblivious transfer from packet reordering
ICISC'11 Proceedings of the 14th international conference on Information Security and Cryptology
Efficient buffering and scheduling for a single-chip crosspoint-queued switch
Proceedings of the eighth ACM/IEEE symposium on Architectures for networking and communications systems
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We present a classification methodology and a measurement study for out-of-sequence packets in TCP connections going over the Sprint IP backbone. Out-of-sequence packets can result from many events including loss, looping, reordering, or duplication in the network. It is important to quantify and understand the causes of such out-of-sequence packets since it is an indicator of the performance of a TCP connection, and the quality of its end-end path. Our study is based on passively observed packets from a point inside a large backbone network--as opposed to actively sending and measuring end-end probe traffic at the sender or receiver. A new methodology is thus required to infer the causes of a connection's out-of-sequence packets using only measurements taken in the "middle" of the connection's end-end path. We describe techniques that classify observed out-of-sequence behavior based only on the previously- and subsequently-observed packets within a connection and knowledge of how TCP behaves. We analyze numerous several-hour packet-level traces from a set of OC-12 and OC-48 links for tens of millions connections generated in nearly 7600 unique ASes. We show that using our techniques, it is possible to classify almost all out-of-sequence packets in our traces and that we can quantify the uncertainty in our classification. Our measurements show a relatively consistent rate of out-of-sequence packets of approximately 4%. We observe that a majority of out-of-sequence packets are retransmissions, with a smaller percentage resulting from in-network reordering.