Massive Data Sets Proceedings of a Workshop (1996) / Chapter Skim
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Analyzing Telephone Network Data
Analyzing Telephone Network Data
Pages 81-92
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From page 81... ...
As a result, telephone companies are very interested in the health of their portion of the CCS Network. At BeDcore, we help network providers keep their part of the CCS Network running smoothly by testing vendor equipment and by monitoring live networks.
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Collecting ah the data from a network provider's live network would require monitoring several thousand communication links, and is beyond the capacity of our monitoring equipment. In North America, a protocol called Signaling System Number 7 (SS7, ANST (1987~)
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From page 83... ...
The overall packet arrival process shows signs of Tong range dependence, and is not wed modeled by a time-inhomogeneous Poisson process. Plots such as this also suggest that it is virtually impossible to find a stationary busy hour, the typical engineering period in traditional telephone networks.
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cl)
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From page 85... ...
· sort/merge. The raw data files produced by NSTS need to be sorted into time order, and sorted files from multiple NSTS's need to be merged.
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I A fitter to do a cumulative sum of the result of the previous step and print out the value of the sum at a reasonable number of equally spaced times.
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From page 87... ...
Network planners, who are interested in traffic trends over months or years. The network nodes themselves provide gross traffic data.
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Our filter building blocks allow us to design software tools to fit each application. Because the applications share a common infrastructure, the programming effort required is not large.
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However, there are monsters in our future' We are testing a second generation of SS7 data collection equipment that can store roughly 55 gigabytes of data from 96 (bidirectional) communication links at a single STP site without manual intervention.
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From page 90... ...
(1993~. Analyzing Telecommunications Traffic Data from Working Common Channel Signaling Subnetworks.
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From page 91... ...
. Self-Similarity Through High-Variability: Statistical Analysis of Ethernet LAN Traffic at the Source Level.
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