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Figure 104 Evolution of the marginal rate distribution cell (per-cell bandwidth) As a result, in the total SA under analysis covering hundreds of parallel connections spanning several cells the correlation between the rates of individual connections is very low, and the shape of the total traf c distribution is dominated by the arrival/departure process of the connections, assumed independent at a rst approximation Since higher traf c during the day means essentially more active MSs and more parallel connections, this translates into a marginal rate distribution with increasing mean, variance and symmetry, as is typical with the superposition of many independent On/Off sources Without any common bottleneck, such a trend would be maintained also during the peak hour (evening and early night), with more variance and more symmetry as in the top graph of Figure 104 Instead, when the bottleneck is in place (bottom graph of Figure 10.

198 6

4) it introduces an additional limit on the total rate of the whole SA whose effect becomes stronger as the total traf c approaches the bottleneck capacity At this point two phenomena take place First, due to the TCP congestion control mechanisms, the bottleneck introduces correlation between the rates of the individual connections Secondly, an additional controlloop emerges from the user behaviour: users will delay the next download until the current one is completed, and arguably some users will abandon the network if the perceived quality degrades below what they consider to be the acceptable level As a result, the user behaviour contributes to modulation of the number of parallel connections during the congestion period.

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The joint effect of these two control loops (TCP congestion control and user behaviour) is that the total marginal rate distribution becomes compressed towards the capacity limit: consequently, its total variance diminishes, and the hard-limit on the upper tail but not on the lower one leaves the distribution left-skewed Diagnosis Method The basic idea of our work is that by simply observing the evolution of the marginal rate distribution during one day cycle, it is possible to infer the presence of a bottleneck, which.

d----1 owner group 0 Nov 22 14:38 Softlib ----1 owner group 5095 Oct 20 1993 support-phones.txt ----1 owner group 802 Aug 25 1994 WhatHappened.txt 226 Transfer complete. 1407 bytes received in 0.99 seconds (1.42 Kbytes/sec)

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