Fundamental characteristics and arrival curve modeling of live streaming traffic via 5G NR system based on OAI platform

Yuehong Gao; Alimu Kuerban; Xiaoqi Wang; Xiaohang Zhang

doi:10.1117/12.3009305

16 October 2023 Fundamental characteristics and arrival curve modeling of live streaming traffic via 5G NR system based on OAI platform

Yuehong Gao, Alimu Kuerban, Xiaoqi Wang, Xiaohang Zhang

Author Affiliations +

Proceedings Volume 12803, Fifth International Conference on Artificial Intelligence and Computer Science (AICS 2023); 1280315 (2023) https://doi.org/10.1117/12.3009305
Event: 2023 5th International Conference on Artificial Intelligence and Computer Science (AICS 2023), 2023, Wuhan, China

Abstract

In order to better guarantee different quality of service requirements for different types of 5G network traffic, the characteristics should be studied and modeled for each type of traffic carried via 5G network. In this paper, we report a measurement-based study, which includes 5G network traffic data collection, analysis and modeling. To better extract the behavioral characteristics of 5G network traffic, we conduct the collection of traffic data from the 5G new radio (NR) system based on OpenAirInterface (OAI) platform and universal software radio peripheral (USRP). In this paper, three types of traffic carried via 5G network are collected and analyzed. For basic traffic characteristics, the traffic rates and the probability density distribution of packet length and packet interval are analyzed. For traffic modeling, the concept of cumulative arrival process is adopted and the arrival curve model is derived based on network calculus.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yuehong Gao, Alimu Kuerban, Xiaoqi Wang, and Xiaohang Zhang "Fundamental characteristics and arrival curve modeling of live streaming traffic via 5G NR system based on OAI platform", Proc. SPIE 12803, Fifth International Conference on Artificial Intelligence and Computer Science (AICS 2023), 1280315 (16 October 2023); https://doi.org/10.1117/12.3009305

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