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Metric \ Monitor Targetpinger to pinger-raspberrypinger-raspberry to pingerpinger to sitkapinger-raspberry to sitkasitka to pingersitka to pinger-raspberrypinger to CERNpinger-raspberry to CERN
Time periodJune 17 - July 13, 2015June 17 - July 13, 2015June 17 - July 14, 2015June 17 - July 14July 15 - July 16 2015July 15 - July 16 2015June 17 - July 12, 2015June 17 - July 12, 2015
Samples108901085010900108508208201090010900

Min RTT

0.43 ms0.41 ms22 ms22.3 ms22 ms22.4 ms150 ms151 ms
Avg RTT0.542 ms0.529 ms23.9 ms23.827 ms22.303 ms22.709 ms150.307 ms151.024 ms

Max RTT

1.15 ms20.8 ms761 ms334 ms26.3 ms25.9 ms288 ms183 ms
Stdev0.055 ms0.540 ms9.58 ms9.60 ms0.219 ms0.222 ms9.572 ms9.594 ms
Median RTT0.542 ms0.51 ms22.3 ms22.7 ms22.3 ms22.7 ms150 ms151 ms
25%

0.514 ms

0.48 ms22.2 ms22.69 ms22.3 ms22.8 ms149.99 ms150.99 ms
75%0.564 ms0.532 ms22.4 ms22.8 ms22.19 ms22.59 ms151 ms151 ms
IQR0.05 ms0.052 ms0.2 ms0.11 ms0.113 ms0.210 ms1.01 ms0.01 ms
Min IPD-0.59 ms-20.29 ms-244 ms-235.1 ms

-0.4 ms

-0.39 ms-137 ms

-32 ms

Avg IPD0 ms0 ms0 ms0 ms0 ms0 ms0 ms0
Max IPD0.62 ms20.26 ms268 ms146 ms3.6 ms3.29 ms138 ms32 ms
Median IPD0 ms0 ms0 ms0 ms0 ms0 ms0 ms0 ms
Stdev    0.248 ms0.296 ms  
25% IPD-0.04 ms-0.03 ms-0.1 ms-0.11 ms-0.1 ms-0.1 ms-0.01 ms-0.01 ms
75% IPD0.03 ms0.02 ms0.09 ms0.1 ms0.01 ms0.09 ms0 ms0 ms
IQR IPD0.07 ms0.05 ms0.190 ms0.210 ms0.2 ms0.190ms0.01 ms0.01 ms
Min(abs(IPD))0 ms0 ms0 ms0 ms0 ms0 ms0 ms0 ms
Avg(abs(IPD))0.041 ms0.066 ms0.424 ms0.406 ms0.120 ms0.139 ms0.386 ms0.046 ms
Max(abs(IPD))0.0628ms20.294 ms268 ms235.1 ms4 ms3.29 ms138 ms32 ms
Stdev    0.248 ms0.262 ms  
Median(abs(IPD))0.03ms0.024 ms0.09 ms0.1 ms0.1 ms0.09 ms0 ms0 ms
25%(abs(IPD))0.01ms0.008 ms0.01 ms0.01 ms-0.01 ms-0.01 ms0.01 ms0.01 ms
75%(abs(IPD))0.058 ms0.05 ms0.1 ms0.19 ms0.1 ms0.19 ms1 ms0 ms
IQR(abs(IPD)0.048 ms0.042 ms0.09 ms0.11 ms0.11 ms0.2 ms0.009 ms0.01 ms
Loss0%0%0%0.008%0%0%0%0%

Kolmogorov-Smirnov Test

The Kolmogorov-Smirnov test (KS-test) tries to determine if two datasets differ significantly. The KS-test has the advantage of making no assumption about the distribution of data. In other words it is non-parametric and distribution free. The method is explained here and makes use of an Excel tool called "Real Statiscs". The tests were made using the raw data and distributions, both methods had similar results except for the 100Bytes Packet that  had a great difference in the results. The results using raw data says both samples does not come from the same distribution with a significant difference, however if we use distributions the result says that only the 1000Bytes packet does not come from the same distribution. Bellow you will find the graphs for the distributions that were created and the cumulative frequency in both cases plotted one above other (in order to see the difference between the distributions).

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