Periodic Reporting for period 2 - CogNet (Building an Intelligent System of Insights and Action for 5G Network Management)
Reporting period: 2016-07-01 to 2017-12-31
Overall WP1 ensured to collaboration between the partners from all of the work packages in the form of weekly phone conferences, quarterly plenary and technical face to face meetings and various workshops that only involved relevant partners.
Work Package 2 concentrated on identifying and defining a set of challenges, use cases and scenarios and their requirements, related to the 5G network, specifically from a network management perspective.
The first deliverable D2.1 introduced six use cases of CogNet based on the challenges of the future 5G network management. D2.1 also introduced a total of eleven initial scenarios all pivoting around the use cases in order to facilitate more specific research questions of high impact value in a real life situation. These were reduced to seven scenarios in Deliverable 2.2.
Work Package 3 focuses on design and implementation of algorithms within the CogNet Smart Engine as well as integration and adaptation of off-the-shelf state-of-the-art machine learning modules.
The main outputs of WP3 have been presented in detail in four deliverables.
Work Package 4 aimed at researching and developing smart real-time analytics techniques for optimizing the performance of Virtual Network Functions (VNFs) in terms of energy efficiency, quality of service and resource elasticity by means of orchestration mechanisms.
Work Package 5 aimed at reaching an appropriate set of security mechanisms based on the machine learning addressing the dynamic network function environment of the software networks on top of the cloud. Each of the WP phases was reflected in the form of a deliverable.
Work Package 6 designed and implemented the CogNet Common Infrastructure. A set of scripts and Ansible playbooks which allows any network manager to deploy the full CogNet infrastructure ready to capture data, analyse specific key features and provide actuation suggestion according to the identified or predicted networking issues and the defined actuation providing a best-practice reference platform for developing cognitive management solutions with machine learning.
WP6 has also implemented a set of different demonstrators which meet the requirements and specific 5G challenges, explored in WP4 and WP5. The demonstrators, selected from real business plans from partners, generate or use representative datasets to meet target 5G challenges.
Work Package 7 was focused on guaranteeing a strong impact of the project achievements in the most relevant research and industrial communities, spanning across several categories of stakeholders in the cloud service provider, 5G and Machine learning areas by the use of the following mediums:
- Website and Social Media channels
- Communication and Dissemination
- Business exploitation
The dissemination plan of the CogNet partners included publishing high-quality papers in major international conferences and journals in the area of networking, security and autonomic systems. The consortium's final exploitation strategy has been periodically captured throughout the life time of the project and has the final strategy documented in the deliverable D7.9 where each partner has provided a plan to exploit the achievements of the CogNet project.