In this work we address the problem of inferring the presence of a capacity bottleneck from passive measurements in a 3G mobile network. The study is based on one month of packet traces collected in the UMTS core network of mobilkom austria AG & Co KG, the leading mobile telecommunications provider in Austria, EU. During the measurement period a bottleneck link in the UMTS core network was revealed and removed, therefore the traces enable the accurate analysis and comparison of the traffic behavior in the two network conditions: with and without a capacity bottleneck. Two approaches to bottleneck detection are investigated. The first one is based on the signal analysis of the marginal rate distribution of the traffic aggregate along one day cycle. Since TCP-controlled traffic dominates the overall traffic mix, the presence of a bottleneck strains the aggregate rate distribution and compresses it against the capacity limit during the peak hour. The second approach is based on the analysis of several TCP performance parameters, e.g. estimated frequency of retransmissions. Such statistics are unstable due to the presence of few top users, but this effect can be counteracted with simple filtering methods. Both approaches are validated via simulations. Our results show that both approaches can be used to provide early warning about future occurrences of capacity bottlenecks, and can complement other existing monitoring tools in the operation of a production network.

Diagnosis of Capacity Bottlenecks via Passive Monitoring in 3G Networks: an Empirical Analysis

RICCIATO, FABIO;
2007

Abstract

In this work we address the problem of inferring the presence of a capacity bottleneck from passive measurements in a 3G mobile network. The study is based on one month of packet traces collected in the UMTS core network of mobilkom austria AG & Co KG, the leading mobile telecommunications provider in Austria, EU. During the measurement period a bottleneck link in the UMTS core network was revealed and removed, therefore the traces enable the accurate analysis and comparison of the traffic behavior in the two network conditions: with and without a capacity bottleneck. Two approaches to bottleneck detection are investigated. The first one is based on the signal analysis of the marginal rate distribution of the traffic aggregate along one day cycle. Since TCP-controlled traffic dominates the overall traffic mix, the presence of a bottleneck strains the aggregate rate distribution and compresses it against the capacity limit during the peak hour. The second approach is based on the analysis of several TCP performance parameters, e.g. estimated frequency of retransmissions. Such statistics are unstable due to the presence of few top users, but this effect can be counteracted with simple filtering methods. Both approaches are validated via simulations. Our results show that both approaches can be used to provide early warning about future occurrences of capacity bottlenecks, and can complement other existing monitoring tools in the operation of a production network.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11587/107473
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