The SELFNET Approach for Autonomic Management in an NFV/SDN Networking Paradigm
Author(s) -
Pedro Neves,
Rui Calé,
Mário Rui P. F. N. Costa,
Carlos Parada,
Bruno Parreira,
José M. Alcaraz Calero,
Qi Wang,
James Nightingale,
Enrique ChirivellaPerez,
Wei Jiang,
Hans D. Schotten,
Κωνσταντίνος Κουτσόπουλος,
Anastasius Gavras,
Maria João Barros
Publication year - 2016
Publication title -
international journal of distributed sensor networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 53
eISSN - 1550-1477
pISSN - 1550-1329
DOI - 10.1155/2016/2897479
Subject(s) - computer science , orchestration , software defined networking , network management , computer network , virtualization , distributed computing , layer (electronics) , application layer , network functions virtualization , network architecture , networking hardware , cloud computing , autonomic computing , software , operating system , art , musical , chemistry , organic chemistry , visual arts
To meet the challenging key performance indicators of the fifth generation (5G) system, the network infrastructure becomes more heterogeneous and complex. This will bring a high pressure on the reduction of OPEX and the improvement of the user experience. Hence, shifting today's manual and semi-automatic network management into an autonomic and intelligent framework will play a vital role in the upcoming 5G system. Based on the cutting-edge technologies, such as Software-Defined Networking and Network Function Virtualization, a novel management framework upon the software-defined and Virtualized Network is proposed by EU H2020 SELFNET project. In the paper, the reference architecture of SELFNET, which is divided into Infrastructure Layer, Virtualized Network Layer, SON Control Layer, SON Autonomic Layer, NFV Orchestration and Management Layer, and Access Layer, will be presented.
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