2006
DOI: 10.1049/el:20062423
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Challenging the square-root law for TCP send-rate

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“…Furthermore, according to [Baccelli and McDonald 2005], inversesquare root proportionality is also valid with non-persistent flows. Nevertheless, the inverse-square root law for TCP throughput prediction is not universal; if packet loss is sufficiently small, the steady-state TCP throughput prediction can be obtained with the proportion 1/p (linear regime) instead of 1/ √ p if p is not greater than a value of p max , as stated in [Zaragoza 2006]. Just as an additional example, regarding any TCP lossbased congestion control protocol, a more general formula is stated by [Xu et al 2004] in R(p) = 1 RT T c p y ; R(p) is the response function representing the steady-state sending rate of the protocol in the unit of packets per RT T , stated as a function of packet loss (p), being c and y constants depending on the implementation.…”
Section: Tcp Throughput Predicitionmentioning
confidence: 99%
“…Furthermore, according to [Baccelli and McDonald 2005], inversesquare root proportionality is also valid with non-persistent flows. Nevertheless, the inverse-square root law for TCP throughput prediction is not universal; if packet loss is sufficiently small, the steady-state TCP throughput prediction can be obtained with the proportion 1/p (linear regime) instead of 1/ √ p if p is not greater than a value of p max , as stated in [Zaragoza 2006]. Just as an additional example, regarding any TCP lossbased congestion control protocol, a more general formula is stated by [Xu et al 2004] in R(p) = 1 RT T c p y ; R(p) is the response function representing the steady-state sending rate of the protocol in the unit of packets per RT T , stated as a function of packet loss (p), being c and y constants depending on the implementation.…”
Section: Tcp Throughput Predicitionmentioning
confidence: 99%