### Table 4: All burst sources; the number of sources and the burstiness vary.

1992

"... In PAGE 6: ... To keep the burstiness fixed, the cell separation must be increased times when the number of sources increases times. Table4 shows that as the number of sources increases by a factor of four and the burstiness stays the same, the block loss rate is reduced by 101. As the number of sources increases by a... ..."

Cited by 10

### Table 3. Results with bursty source, very short bursts.

2002

### Table 6: Burstiness of Loss: for the WRN source on Dec 11,1995

1996

"... In PAGE 14: ... Then, we generalize our observations by showing summary statistics for all of the datasets. Table6 shows statistics for data collected on Dec 11, 1995. The source was World Radio Net- work which transmitted packets at 80ms: intervals.... In PAGE 14: ... The coefficient of variation of the burst length is defined as c = q E[(b ? b)2] b (3) where b is the burst length or the number of consecutive losses and b is the mean burst length. Table6 also partially describes the distributions of the burst length by including the median, the 75 percentile, the 99 percentile and the maximum burst length, for all receivers. The table shows what per- centage of the total loss is in bursts of length greater than 100.... ..."

Cited by 204

### Table 6: Burstiness of Loss: for the WRN source on Dec 11,1995

1996

"... In PAGE 14: ... Then, we generalize our observations by showing summary statistics for all of the datasets. Table6 shows statistics for data collected on Dec 11, 1995. The source was World Radio Net- work which transmitted packets at 80ms: intervals.... In PAGE 14: ... The coefficient of variation of the burst length is defined as c = q E[(b ? b)2] b (3) where b is the burst length or the number of consecutive losses and b is the mean burst length. Table6 also partially describes the distributions of the burst length by including the median, the 75 percentile, the 99 percentile and the maximum burst length, for all receivers. The table shows what per- centage of the total loss is in bursts of length greater than 100.... ..."

Cited by 204

### Table 2 99.9-percentile virtual-waiting time: bursty sources Bandwidth utilization 10 sources 1000 sources

2005

### Table 6: Burstiness of Loss: source-WRN, on Dec 11,1995

1996

"... In PAGE 5: ... Then, we generalize our observations by showing summary statistics for all of the datasets. Table6 shows statistics for data collected on Dec 11, 1995. The source was World Radio Network which transmitted pack- ets at 80ms: intervals.... In PAGE 5: ...1 1 0 5 10 15 20 25 30 35 40 45 50 Probability of bursts of length b length of loss burst: b Distribution of length of loss bursts for receiver alps Figure 5: Distribution of loss burst length: alps(Georgia) where b is the burst length or the number of consecutive losses and b is the mean burst length. Table6 also partially describes the distributions of the burst length by including the 99-percentile and the maximum burst length, for every receiver. For all receivers, both the median and the 75-percentile burst length were found to be 1, indicating the predominance of solitary losses.... ..."

Cited by 204

### Table 5 presents the measured expansion rates using the back-to-back COST 224 source.

"... In PAGE 15: ... Table5 : Mean burst expansion, COST 224 source with back-to-back burst Figure 8 (d) shows the burst expansion for the bursty source E. Bursts expand more quickly for the bursty source E than for bursty source B (not shown), for the same mean load.... ..."

### Table 2 : E ect of Tra c Burstiness on Performance Measures The burstiness of the source increases with M causing the log-tail of the queue length distribution to be attened. Except for the values of PrfL ng with n near 0, the curves with di erent M-values are linear on a logarithm scale with slopes whose magnitudes decrease with M.

"... In PAGE 9: ...M 1 2 4 8 S = 1 106 143 274 626 S = 2 106 143 274 627 S = 4 106 143 275 628 S = 8 107 145 278 633 Table 1 : Bu er Requirements to Achieve CLP lt; 10?9 Figure 3 illustrates the e ect of bursty tra c on the tail distribution of the entry monitor with parameters (R; T; S) = (66; 600; 4). Table2 contains i) descriptors of the arrival process - expectation, variance, squared coe cient of variation (CV 2) and ii) performance measures of the monitor - expectation and variance of the queue length, - the size of the bu er N(10?9) required to achieve a cell-loss probability 10?9, and - the root # of 0 = zR ? PT (z) outside of the unit disk of smallest modulus. 16 32 48 64 80 0.... ..."