DeepNFV: A Lightweight Framework for Intelligent Edge Network Functions Virtualization | Zendy

Liangzhi Li | Zendy; Kaoru Ota | Zendy; Mianxiong Dong | Zendy

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DeepNFV: A Lightweight Framework for Intelligent Edge Network Functions Virtualization

Author(s) -

Liangzhi Li,

Kaoru Ota,

Mianxiong Dong

Publication year - 2018

Publication title -

ieee network

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 2.546

H-Index - 129

eISSN - 1558-156X

pISSN - 0890-8044

DOI - 10.1109/mnet.2018.1700394

Subject(s) - computer science , virtualization , container (type theory) , server , network functions virtualization , implementation , overhead (engineering) , enhanced data rates for gsm evolution , distributed computing , deep learning , computer architecture , operating system , artificial intelligence , software engineering , cloud computing , mechanical engineering , engineering

Traditional Network Functions Virtualization (NFV) implementations are somehow too heavy and do not have enough functionality to conduct complex tasks. In this work, we propose a lightweight NFV framework named DeepNFV, which is based on the Docker container running on the network edge, and integrates state-of-the-art deep learning models with NFV containers to address some complicated problems, s...

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