Principal Component Analysis of Mobility Data from an Operational GPRS Network

Charlotte  Dumard; Fabio  Ricciato; Thomas   Zemen

1st International ICST Conference on Communications and Networking in China

Research Article

Principal Component Analysis of Mobility Data from an Operational GPRS Network

Cite: BibTeX Plain Text

@INPROCEEDINGS{10.1109/CHINACOM.2006.344731,
    author={Charlotte  Dumard and Fabio  Ricciato and Thomas   Zemen},
    title={Principal Component Analysis of Mobility Data from an Operational GPRS Network},
    proceedings={1st International ICST Conference on Communications and Networking in China},
    publisher={IEEE},
    proceedings_a={CHINACOM},
    year={2007},
    month={4},
    keywords={},
    doi={10.1109/CHINACOM.2006.344731}
}

Charlotte Dumard
Fabio Ricciato
Thomas Zemen
Year: 2007
Principal Component Analysis of Mobility Data from an Operational GPRS Network
CHINACOM
IEEE
DOI: 10.1109/CHINACOM.2006.344731

Charlotte Dumard^1,2^,*, Fabio Ricciato^1,2^,*, Thomas Zemen^1,2^,*

1: ftw. Forschungszentrum TelekommunikationWien
2: Donau-City-Str. 1/3 A-1220 Wien, Austria

*Contact email: dumard@ftw.at, ricciato@ftw.at, zemen@ftw.at

Abstract

We present a preliminary analysis of mobility data collected from an operational GPRS network. The input data are time-series counting the number of mobile stations present in each of 126 sample routing areas at equally spaced instants (5 min) during one full week. The time-series were extracted from packet-level traces captured by passively monitoring a subset of the Gb links of the network of Mobilkom Austria AG & Co KG during October 2004. We apply the principal component analysis (PCA) to this dataset. The PCA offers a simple method for classifying the routing areas into two main groups, residential and business areas, plus a few "atypical" ones. Additionally, we address the problem of robustness of the PCA to temporary local gaps in the input data

Published: 2007-04-10
Publisher: IEEE

: http://dx.doi.org/10.1109/CHINACOM.2006.344731