A passive state-machine approach for accurate analysis of TCP out-of-sequence segments
ACM SIGCOMM Computer Communication Review, 2006•dl.acm.org
In this paper we describe a new tool being made available to the networking research
community for passive analysis of TCP segment traces. The purpose of the tool is to provide
more complete and accurate classification of out-of-sequence segments than those provided
by prior tools. One of the crucial factors that limits the accuracy of prior tools is that these do
not incorporate variations across TCP implementations (for different operating systems) that
have different parameters (eg, timer granularity, minimum RTO, duplicate ACK thresholds …
community for passive analysis of TCP segment traces. The purpose of the tool is to provide
more complete and accurate classification of out-of-sequence segments than those provided
by prior tools. One of the crucial factors that limits the accuracy of prior tools is that these do
not incorporate variations across TCP implementations (for different operating systems) that
have different parameters (eg, timer granularity, minimum RTO, duplicate ACK thresholds …
In this paper we describe a new tool being made available to the networking research community for passive analysis of TCP segment traces. The purpose of the tool is to provide more complete and accurate classification of out-of-sequence segments than those provided by prior tools. One of the crucial factors that limits the accuracy of prior tools is that these do not incorporate variations across TCP implementations (for different operating systems) that have different parameters (e.g., timer granularity, minimum RTO, duplicate ACK thresholds, etc.) or algorithms that influence what can be inferred about out-of-sequence segments. Our tool explicitly accounts for implementation-specific details in four prominent TCP stacks (Windows, Linux, FreeBSD/Mac OS-X, and Solaris). We validate our tool through several controlled experiments with instances of all four OS-specific implementations used in the analysis. We then run this tool on packet traces of 52 million Internet TCP connections collected from 5 different locations and present the results. We also include comparisons with results from running selected prior tools on the same traces.
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