SOFTNETICS 2018 - IEEE 2018 IEEE International Workshop on Softwarized Networks Analytics

Network softwarization with SDN and NFV is in the core of the major shifts in networking. Thanks to enhanced programmability, all related technologies promise a higher level of flexibility, a stronger coupling between network and services, applications and users in order to offer high-end and customized services. However, providing only the technological enablers is not enough to support innovation in telecommunication networks and on top of them, new methods and mechanisms have to be established to fully take advantage of the offered capabilities.
For example, heuristic based optimization techniques have proven to be successful in deriving network policies to configurations of softwarized network elements. In parallel, the big data era stimulates the use of artificial intelligence, Machine Learning (ML) and data mining techniques as well as the apparition of batch and streaming data analytic frameworks and paradigms. Deep learning recently gains in popularity and paves the way to more powerful application of ML to various problems. Many areas can leverage all this type of analytics to handle the data explosion phenomenon or increasing complexity of problems to solve in an efficient and valuable way, as for example to detect or even predict threats, decide on mitigation strategies, provision resources for QoS, etc.
On one hand, the objectives of advanced mechanisms would be to support better decisions for softwarized networks in a fully automated way or to assist or guide human operators with strong and enhanced cooperation with new visualisation approaches including virtual reality. A major constraint that would appear is the ability to operate in real-time and to be compatible with requirements of the softwarized networks regarding its responsiveness to configuration modifications, the programmability expressiveness, which may limit the number and types of allowed operations, and the overhead induced.
On the other hand, data-driven techniques suppose the acquisition, i.e. the monitoring, and the processing of data. The sources of data could be located within the targeted network to be managed or outside. There are important challenge to be addressed on how to efficiently collect and process data of a softwarized network and even how to integrated data from external sources in order to improve the derived knowledge.
SOFTNETICS 2018 is a dedicated venue for bringing together students, researchers and practitioners from academia and industry who share common interests in all types of analytics methods applied with application to the softwarization of network in any functional domain. Theoretical approaches, practical experimentations and papers highlighting future trends and challenges are welcomed