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We address the problem of detecting ''anomalies'' in the network traffic produced by a large population of end-users following a distribution-based change detection approach. In the considered scenario, different traffic variables are monitored at different levels of temporal aggregation (timescales), resulting in a grid of variable/timescale nodes. For every node, a set of per-user traffic counters...
In this work we present a simple toy-model that is able to explain certain empirical observations reported in a set of previous papers by Hohn et al. about the wavelet spectrum of real traffic traces. Therein, the authors found that the wavelet spectrum is substantially invariant to flow scrambling and truncation. Such finding suggested that super-flow structures above the transport layer - i.e.,...
In this work we present a novel scheme for statistical-based anomaly detection in 3G cellular networks. The traffic data collected by a passive monitoring system are reduced to a set of per-mobile user counters, from which time-series of unidimensional feature distributions are derived. An example of feature is the number of TCP SYN packets seen in uplink for each mobile user in fixed-length time...
In this contribution we address the problem of using cellular network signaling for inferring real-time road traffic information. We survey and categorize the approaches that have been proposed in the literature for a cellular-based road monitoring system and identify advantages and limitations. We outline a unified framework that encompasses UMTS and GPRS data collection in addition to GSM, and prospectively...
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