Autonomic Network Management for Software-Defined and Virtualized 5G Systems

Conference: European Wireless 2017 - 23th European Wireless Conference
05/17/2017 - 05/19/2017 at Dresden, Germany

Proceedings: European Wireless 2017

Pages: 6Language: englishTyp: PDF

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Authors:
Jiang, Wei (German Research Center for Artificial Intelligence (DFKI), Trippstadter Str. 122, 67663 Kaiserslautern, Germany & Technische Universität Kaiserslautern, Germany)
Strufe, Mathias (German Research Center for Artificial Intelligence (DFKI), Trippstadter Str. 122, 67663 Kaiserslautern, Germany)
Schotten, Hans (Technische Universität Kaiserslautern, Germany)

Abstract:
The Fifth Generation (5G) system is envisioned to become more complicated, which imposes a great challenge on network management. But today’s manual and semi-automatic managing approaches are already costly and time-consuming. Thanks to new technologies, such as software-defined networking and network function virtualization, a possibility of autonomic management is opened for the 5G system. In this context, a nov- el management framework in software-defined and virtualized network is proposed by the SELFNET project so as to lower operational expenditure, improve user’s experience and reduce time-to-market of services. As a key part of this framework, an Autonomic Manager (AM) is designed to provide the network intelligence by means of machine learning techniques. In this paper, the functionality and mechanism of the AM, as well as an intelligence control loop, are presented. A 5G test-bed established to demonstrate the autonomic management, along with some results on collecting and selecting network metrics, are illustrated.