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dc.contributor.authorBarman, Dhimanen_US
dc.contributor.authorMatta, Ibrahimen_US
dc.date.accessioned2011-10-20T04:12:50Z
dc.date.available2011-10-20T04:12:50Z
dc.date.issued2003-05-16en_US
dc.identifier.urihttp://hdl.handle.net/2144/1507
dc.description.abstractThe Transmission Control Protocol (TCP) has been the protocol of choice for many Internet applications requiring reliable connections. The design of TCP has been challenged by the extension of connections over wireless links. We ask a fundamental question: What is the basic predictive power of TCP of network state, including wireless error conditions? The goal is to improve or readily exploit this predictive power to enable TCP (or variants) to perform well in generalized network settings. To that end, we use Maximum Likelihood Ratio tests to evaluate TCP as a detector/estimator. We quantify how well network state can be estimated, given network response such as distributions of packet delays or TCP throughput that are conditioned on the type of packet loss. Using our model-based approach and extensive simulations, we demonstrate that congestion-induced losses and losses due to wireless transmission errors produce sufficiently different statistics upon which an efficient detector can be built; distributions of network loads can provide effective means for estimating packet loss type; and packet delay is a better signal of network state than short-term throughput. We demonstrate how estimation accuracy is influenced by different proportions of congestion versus wireless losses and penalties on incorrect estimation.en_US
dc.description.sponsorshipNational Science Foundation (ANI-0095988, EIA-0202067, ITR ANI-0205294); Sprint Labs; Motorola Labsen_US
dc.language.isoen_USen_US
dc.publisherBoston University Computer Science Departmenten_US
dc.relation.ispartofseriesBUCS Technical Reports;BUCS-TR-2003-011en_US
dc.subjectTCPen_US
dc.subjectCongestion controlen_US
dc.subjectError controlen_US
dc.subjectBinary hypothesis testingen_US
dc.subjectMaximum likelihood radio testen_US
dc.subjectGaussian distributionen_US
dc.subjectWireless linksen_US
dc.subjectSimulationen_US
dc.titleHow Well Can TCP Infer Network State?en_US
dc.typeTechnical Reporten_US


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