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Van-Giang Nguyen

Researcher at Karlstad University

Publications -  17
Citations -  588

Van-Giang Nguyen is an academic researcher from Karlstad University. The author has contributed to research in topics: Radio access network & Network packet. The author has an hindex of 7, co-authored 17 publications receiving 494 citations. Previous affiliations of Van-Giang Nguyen include Hanoi University of Science and Technology & Soongsil University.

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Journal ArticleDOI

SDN/NFV-Based Mobile Packet Core Network Architectures: A Survey

TL;DR: This survey aims at providing a comprehensive survey of state-of-the-art research work, which leverages SDN and NFV into the most recent mobile packet core network architecture, evolved packet core.
Journal ArticleDOI

SDN and Virtualization-Based LTE Mobile Network Architectures: A Comprehensive Survey

TL;DR: An overview of SDN, network virtualization, and network function virtualization is provided, and an in-depth analysis about changes related to protocol operation and architecture when adopting SDN and virtualization in mobile networks is presented.
Journal ArticleDOI

Proposal and evaluation of SDN‐based mobile packet core networks

TL;DR: This work provides detailed analyses of five procedures that commonly occur in LTE/EPC architectures and introduces a new Openflow‐enabled EPC (OEPC) architecture that shows that the data management of these procedures is simpler relative to traditional LTE/ EPC.
Proceedings ArticleDOI

Slicing the next mobile packet core network

TL;DR: V-Core, a new architecture for the mobile packet core network which is based on Software Defined Networking and Network Function Virtualization is described and a MobileVisor is introduced which is a machine to slice the above mobile packets core network into different control platforms according to either different mobile operators or different technologies.
Journal ArticleDOI

Modeling and experimenting combined smart sleep and power scaling algorithms in energy-aware data center networks

TL;DR: A new energy saving scheme that combines smart sleeping and power scaling algorithms and a platform for in-depth analysis of energy-aware data center networks, which is a combination of hardware testbed and emulation are presented.