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As it is happening in many fields that need efficient and effective classification of data, Machine Learning (ML) is becoming increasingly popular in network management and monitoring. In general we can say that ML algorithms are complex, therefore better suited for execution in the centralized control plane of modern networks, but are also heavily reliant on data, that are necessarily collected in the data plane. The inevitable consequence is that may arise the need to transfer lots of data from the data plane to the control plane, with the risk to cause congestion on the control communication channel. This may turn into a major drawback, since congestion on the control channel may have a significant impact on network operations. Therefore it is of paramount importance to design systems capable of minimizing the interaction between data and control planes while ensuring good monitoring performance. The most recent generation of data plane programmable switches supporting the P4 language can help mitigate this problem by preprocessing traffic data at line rate. In this manuscript we follow this approach and propose P4RTHENON: an architecture to distill in the data plane the relevant information to be mirrored to the control plane, where complex analysis can be performed. P4RTHENON leverages the P4-native support for runtime data plane pipeline reconfiguration to minimize the interaction between data and control planes while ensuring good monitoring performance. We tested our scheme on the volumetric DDoS detection use case: P4RTHENON reduces the volume of exchanged data by almost 75% compared to a pure control-plane-based solution, guarantees low memory consumption in the data plane, and does not degrade the overall DDoS detection capabilities.

In this work we demonstrate the integration of P4 enabled switches with high level AI techniques with the aim to improve efficiency and performance of DDoS detection and mitigation. Powerful ML-based strategies are adopted only when a suspicious behaviour is occurring in the network, and its activation is triggered by a coarser-grained and lightweight strategy fully executable in the data plane.

Today the performance of network services and devices is mainly assessed using Quality of Services (QoS) factors. These provide statistics about the quality of the network behavior but cannot accurately reflect how the unpredictable impairments which might occur in the network end up affecting the perception of the final beneficiary of these services, i.e. the user. This situation arises because QoS-based performance analysis does not capture the combined end-to-end properties of networks and applications. In this paper, we introduce a new network performance methodology based on Quality of Experience benchmarks, whereby we estimate the quality of the service as it is perceived by the user. We illustrate this approach in the context of video streaming services, showing how to evaluate quality degradation in Software Defined Networks. Our approach is better suited to the evaluation of dynamic networks and helps better pinpointing the critical factors that affect the applications the most.

The exploitation of photonic technology through application of switching principles and system concepts in switch implementation, i.e. photonics in switching, is a very challenging topic in the field of optical networking research. Many European research teams have been involved in high quality studies and trials in this field since several years and obtained funding opportunities for joining their expertise within the e-photon/One+ Network of Excellence. This talk aims at presenting how collaborations on photonics in switching research has been organized within e-Photon/One+ and which actions have been finalized for exploitation and dissemination of this knowledge in science and education. The paper will report a description of research contributions from different partners involved in photonics in switching research., QC 20120221

This paper reports the view of the e-Photon/ONe community regarding the research directions in optical transport networks. Results stemming from joint international research activities in the framework of the project are summarized. This summary presents, necessarily, little details, but wants to draw the attention of the reader towards the most advanced research activities ongoing on the broad topics of optical core networks, from wavelength routed network, to optical burst switching and optical packet switching., QC 20120305

This papers reports the advances in optical core networks research coordinated in the framework of the e- photon/ONe and e-photon/ONe+ networks of excellence., QC 20120305

In this paper, promising technologies and a network architecture are presented for future optical packet switched networks. The overall network concept is presented and the major choices are highlighted and compared with alternative solutions. Both long and shorter term approaches are considered, as well as both the wide-area network and multiple-area networks parts of the network. The results presented in this paper were developed in the frame of the research project DAVID (Data And Voice Integration over DWDM) project, funded by the European Commission through the IST-framework.