Prototybe and Report Framework for enabling the encapsulation of NFV and SDN Applications

This deliverable presents the analysis, design and prototype implementation of SELFNET mechanisms and procedures for the encapsulation of Network Function Virtualization (NFV) and Software Defined Network (SDN) applications. These applications are SELFNET sensors and actuators that will support the four use cases defined in the project: self-optimization, self-healing, self-protection and a composed use case combining the previous three. Their encapsulation basically provides common and uniform primitives and procedures to manage their lifecycle (instantiation, configuration, termination, etc.) irrespectively of the specific application logic. In particular, two prototypes are released with this deliverable in support of Virtual Network Functions (VNFs) and SDN application lifecycle management. Ref. Ares(2016)1917050 22/04/2016 Deliverable D2.3 SELFNET H2020-ICT-2014-2/671672 © SELFNET consortium 2016 Page 2 of (99) Disclaimer This document contains material, which is the copyright of certain SELFNET consortium parties, and may not be reproduced or copied without permission. All SELFNET consortium parties have agreed to full publication of this document. The commercial use of any information contained in this document may require a license from the proprietor of that information. Neither the SELFNET consortium as a whole, nor a certain part of the SELFNET consortium, warrant that the information contained in this document is capable of use, nor that use of the information is free from risk, accepting no liability for loss or damage suffered by any person using this information. The EC flag in this press release is owned by the European Commission and the 5G PPP logo is owned by the 5G PPP initiative. The use of the flag and the 5G PPP logo reflects that SELFNET receives funding from the European Commission, integrated in its 5G PPP initiative. Apart from this, the European Commission or the 5G PPP initiative have no responsibility for the content. The research leading to these results has received funding from the European Union Horizon 2020 Programme under grant agreement number H2020-ICT-2014-2/671672.