Algorithmics and modeling aspects of network slicing in 5G and beyonds network: Survey

F Debbabi, R Jmal, LC Fourati, A Ksentini - IEEE Access, 2020 - ieeexplore.ieee.org
One of the key goals of future 5G networks is to incorporate many different services into a
single physical network, where each service has its logical network isolated from other …

Learning combinatorial optimization on graphs: A survey with applications to networking

N Vesselinova, R Steinert, DF Perez-Ramirez… - IEEE …, 2020 - ieeexplore.ieee.org
Existing approaches to solving combinatorial optimization problems on graphs suffer from
the need to engineer each problem algorithmically, with practical problems recurring in …

Machine learning-driven service function chain placement and scaling in MEC-enabled 5G networks

T Subramanya, D Harutyunyan, R Riggio - Computer Networks, 2020 - Elsevier
Abstract 5G mobile network technology promises to deliver unprecedented ultra-low latency
and high data rates, paving the way for many novel applications and services. Network …

On dynamic service function chain reconfiguration in IoT networks

Y Liu, Y Lu, X Li, Z Yao, D Zhao - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
Network function virtualization (NFV) technology continues to gain more attention as a
paradigm shift, and telecommunication services can be flexibly deployed and managed. Any …

A network intelligence architecture for efficient vnf lifecycle management

S Lange, N Van Tu, SY Jeong, DY Lee… - … on Network and …, 2020 - ieeexplore.ieee.org
Network softwarization paradigms such as SDN and NFV provide network operators with
advantages in terms of scalability, cost and resource efficiency, as well as flexibility …

Machine learning for dynamic resource allocation in network function virtualization

S Schneider, NP Satheeschandran… - 2020 6th IEEE …, 2020 - ieeexplore.ieee.org
Network function virtualization (NFV) proposes to replace physical middleboxes with more
flexible virtual network functions (VNFs). To dynamically adjust to ever-changing traffic …

Auto-3P: An autonomous VNF performance prediction & placement framework based on machine learning

M Bunyakitanon, AP Da Silva, X Vasilakos… - Computer Networks, 2020 - Elsevier
We propose Auto-3P, an Autonomous module for Virtual Network Functions Performance
Prediction and P lacement at network cloud and edge facilities based on Machine Learning …

A disaggregated packet processing architecture for network function virtualization

SR Chowdhury, H Bian, T Bai… - IEEE Journal on …, 2020 - ieeexplore.ieee.org
Network Function Virtualization (NFV) promises to reduce the capital and operational
expenditure for network operators by moving packet processing from purpose-built …

Machine learning-based optimal vnf deployment

S Park, HG Kim, J Hong, S Lange… - 2020 21st Asia …, 2020 - ieeexplore.ieee.org
Network Function Virtualization (NFV) environment can deal with dynamic changes in traffic
status with appropriate deployment and scaling of Virtualized Network Function (VNF) …

On construction and performance evaluation of a virtual desktop infrastructure with GPU accelerated

CH Chang, CT Yang, JY Lee, CL Lai, CC Kuo - IEEE Access, 2020 - ieeexplore.ieee.org
More engaging and accessible solutions that offer outstanding user experience are needed.
The virtual desktop infrastructure (VDI) is the first user access part of the cloud. Therefore …