Paulo Gonçalves Inria senior researcher in the project DANTE A joint team of Inria Rhone-Alpes and ENS Lyon (LIP)

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Signal Processing applied to Networks	Dynamic graphs Traffic and Metrology	Description: Metrology of wide-area computer networks (i.e. the deployment of a series of tools allowing for collecting relevant information regarding the system status), is a discipline recently introduced in the context of networks, that undergoes constant developments. In a nutshell, this activity consists in measuring along time, the nature and the amount of exchanged information between the constituents of a system. It is then a matter of using the collected data to forecast the network load evolution, so as to anticipate congestion, and more widely, to guarantee a certain Quality of Service, optimizing resources usage and protocols design. From a statistical signal processing viewpoint, collected traces correspond to (multivariate) time series principally characterized by non-properties: non-gaussianity, non-stationarity, non-linearities, absence of a characteristic time scale (scale invariance). Our research activity is undertaking the development of reliable signal analysis tools aimed at identifying these (non-)properties in the specific context of computer network traffic. In the course, we intend to clarify the importance of granularity of measurements. Another challenge in network metrology is the effectiveness of packet sub-sampling. It means, to collect only a fraction of the overall traffic (supposedly redundant), and to study the possibility of inferring from that partial measurement, the most complete information about the system. Non trivial questions as, which fraction, which sub-sampling rule, adaptativity of this latter, smart sampling, statistical inference, open up a broad scope of investigation. In this research axis, we focus on the following points: Impact of traffic statistical properties (long range dependencies, large deviations...) on the network Quality of Service. Characterization and modeling of the workload volatility of an application for dynamic resource management. Real time identification and classification of transiting flows, according to a sensible typology. Content and users based classification with semi-supervised learning techniques. This research axis is largely covered by Semantic Networking activities carrie out in the common laboratory between INRIA and Alcatel-Lucent (2008-2012), as well as by the ANR project (Programme Blanc) PetaFlow (2009-2012) and the EU FP7 SAIL and GEYSERS projects. Joint work with: Thomas Begin, Shubhabrata Roy (PhD), Marina Sokol (PhD), Patrick Loiseau, Konstantin Avratchenkov
Time-Frequency Analysis Time-Scale Analysis	PDEs applied to TFRs Empirical Mode Decomposition Pseudo affine Wigner Distributions
Wavelets and Fractals Wavelets History by I. Daubechies	Scaling exponents estimation Singularity spectrum estimation Multifractal processes synthesis
Wavelets and Statistics	Diverging moments test Hidden Markov trees Stable laws regression
Other applications	Heart rate variability Remote sensing