Dynamic 5G Network Slicing

5G network slicing is the use of network virtualization to divide single network connections into multiple distinct virtual connections that provide different amounts of resources to different types of traffic. A 5G NS (Network Slicing) instance is composed of a set of virtual network function (VNF) instances to form the end-to-end (E2E) virtual network for the slice to operate independently. The deployment of a NS is a typical virtual network embedding (VNE) problem. The proposed algorithm consists of three parts. First, we devise a Holt-Winters (HW) prediction algorithm to determine traffic demand for network slices. This method is intended to avoid frequent changes in network topology. Second, we propose a virtual network function (VNF) adaptive scaling strategy to reasonably determine the number of VNFs and resources required for network slices to avoid resource wastage. Finally, we develop a proactive online algorithm to deploy network slices.

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Optimal Virtual Network Function Deployment for 5G Network Slicing in a Hybrid Cloud Infrastructure

IEEE Transactions on Wireless Communications ◽

10.1109/twc.2020.3017628 ◽

2020 ◽

Vol 19 (12) ◽

pp. 7942-7956

Author(s):

Antonio De Domenico ◽

Ya-Feng Liu ◽

Wei Yu

Keyword(s):

Virtual Network ◽

Hybrid Cloud ◽

Cloud Infrastructure ◽

Network Slicing ◽

Network Function ◽

5G Network ◽

Virtual Network Function

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Deep Reinforcement Learning-Based Algorithm for VNF-SC Deployment

Security and Communication Networks ◽

10.1155/2021/7398206 ◽

2021 ◽

Vol 2021 ◽

pp. 1-11

Author(s):

Junlei Xuan ◽

Huifang Yang ◽

Xuelin Zhao ◽

Xingpo Ma ◽

Xiaokai Yang

Keyword(s):

Real Time ◽

Optimization Model ◽

Virtual Network ◽

Network Function Virtualization ◽

Prediction Algorithm ◽

Network Service ◽

The Real ◽

Service Chain ◽

Network Function ◽

Virtual Network Function

Network function virtualization (NFV) has the potential to lead to significant reductions in capital expenditure and can improve the flexibility of the network. Virtual network function (VNF) deployment problem will be one of key problems that need to be addressed in NFV. To solve the problem of routing and VNF deployment, an optimization model, which minimizes the maximum index of used frequency slots, the number of used frequency slots, and the number of initialized VNF, is established. In this optimization model, the dependency among the different VNFs is considered. In order to solve the service chain mapping problem of high dynamic virtual network, a new virtual network function service chain mapping algorithm PDQN-VNFSC was proposed by combining prediction algorithm and DQN (Deep Q-Network). Firstly, the real-time mapping of virtual network service chains is modeled into a partial observable Markov decision process. Then, the real-time mapping process of virtual network service chain is optimized by using global and long-term benefits. Finally, the service chain of virtual network function is mapped through the learning decision framework of offline learning and online deployment. The simulation results show that, compared with the existing algorithms, the proposed algorithm has a lower the maximum index of used frequency slots, the number of used frequency slots, and the number of initialized VNF.

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