Traffic analysis for 5G network slice based on machine learning

15Citations
Citations of this article
44Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

With the rise of 5G and Internet of things, especially the key technology of 5G, network slice cuts a physical network into multiple virtual end-to-end networks, each of them can obtain logically independent network resources to support richer services. 5G mobile data and sensor data converge to form a growing network traffic. Traffic explosion evolved into a mixed network type, and network viruses, worms, network theft and malicious attacks are also involved. How to distinguish traffic types, block malicious traffic and make effective use of sensor data under the background of 5G network slice, and also the significance of this study.

Cite

CITATION STYLE

APA

Xie, F., Wei, D., & Wang, Z. (2021). Traffic analysis for 5G network slice based on machine learning. Eurasip Journal on Wireless Communications and Networking, 2021(1). https://doi.org/10.1186/s13638-021-01991-7

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free