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On Estimating End-to-End Network Path Properties (1999)

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by Mark Allman , Vern Paxson
Citations:243 - 14 self
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BibTeX

@MISC{Allman99onestimating,
    author = {Mark Allman and Vern Paxson},
    title = {On Estimating End-to-End Network Path Properties},
    year = {1999}
}

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Abstract

The more information about current network conditions available to a transport protocol, the more efficiently it can use the network to transfer its data. In networks such as the Internet, the transport protocol must often form its own estimates of network properties based on measurements performed by the connection endpoints. We consider two basic transport estimation problems: determining the setting of the retransmission timer (RTO) for a reliable protocol, and estimating the bandwidth available to a connection as it begins. We look at both of these problems in the context of TCP, using a large TCP measurement set [Pax97b] for trace-driven simulations. For RTO estimation, we evaluate a number of different algorithms, finding that the performance of the estimators is dominated by their minimum values, and to a lesser extent, the timer granularity, while being virtually unaffected by how often round-trip time measurements are made or the settings of the parameters in the exponentially-weighted moving average estimators commonly used. For bandwidth estimation, we explore techniques previously sketched in the literature [Hoe96, AD98] and find that in practice they perform less well than anticipated. We then develop a receiver-side algorithm that performs significantly better. 1

Keyphrases

estimating end-to-end network path property    transport protocol    connection endpoint    basic transport estimation problem    bandwidth estimation    receiver-side algorithm    reliable protocol    trace-driven simulation    retransmission timer    literature hoe96    network property    round-trip time measurement    rto estimation    large tcp measurement    minimum value    current network condition    different algorithm    timer granularity    exponentially-weighted moving average estimator   

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