ICAQ: Adaptive QoS System for 5G and Beyond Applications

Liang Zhang; Guoqing Ma; Amer Al-Ghadhban; Shuping Dang; Basem Shihada

doi:10.1109/ICCT50939.2020.9295652

ICAQ: Adaptive QoS System for 5G and Beyond Applications

Liang Zhang, Guoqing Ma, Amer Al-Ghadhban, Shuping Dang, Basem Shihada

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Management of network becomes increasingly difficult due to the rapid proliferation of the Internet of Things (IoT) and heterogeneous demands of applications. To mitigate congestion and maintain a high quality of service (QoS) for application users, we propose an importance-oriented clustering-based QoS system named ICAQ. The system uses unsupervised machine learning to determine and differentiate different application flow priority. The system is proposed to be a generic to both network core features and the application features. An environment monitoring IoT application is implemented as an example to demonstrate the expressive power of ICAQ. Experimental results have verified the effectiveness and efficiency of ICAQ and show a promising potential for using ICAQ for the QoS management of IoT applications in 5G and beyond networks.

Original language	English (US)
Title of host publication	2020 IEEE 20th International Conference on Communication Technology (ICCT)
Publisher	IEEE
ISBN (Print)	978-1-7281-8142-4
DOIs	https://doi.org/10.1109/ICCT50939.2020.9295652
State	Published - 2020

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10.1109/ICCT50939.2020.9295652

https://repository.kaust.edu.sa/bitstream/10754/666661/1/ICAQ.pdf

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@inproceedings{21c053dc53f749bab070476c84906c0f,

title = "ICAQ: Adaptive QoS System for 5G and Beyond Applications",

abstract = "Management of network becomes increasingly difficult due to the rapid proliferation of the Internet of Things (IoT) and heterogeneous demands of applications. To mitigate congestion and maintain a high quality of service (QoS) for application users, we propose an importance-oriented clustering-based QoS system named ICAQ. The system uses unsupervised machine learning to determine and differentiate different application flow priority. The system is proposed to be a generic to both network core features and the application features. An environment monitoring IoT application is implemented as an example to demonstrate the expressive power of ICAQ. Experimental results have verified the effectiveness and efficiency of ICAQ and show a promising potential for using ICAQ for the QoS management of IoT applications in 5G and beyond networks.",

author = "Liang Zhang and Guoqing Ma and Amer Al-Ghadhban and Shuping Dang and Basem Shihada",

note = "KAUST Repository Item: Exported on 2020-12-28",

year = "2020",

doi = "10.1109/ICCT50939.2020.9295652",

language = "English (US)",

isbn = "978-1-7281-8142-4",

booktitle = "2020 IEEE 20th International Conference on Communication Technology (ICCT)",

publisher = "IEEE",

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TY - GEN

T1 - ICAQ: Adaptive QoS System for 5G and Beyond Applications

AU - Zhang, Liang

AU - Ma, Guoqing

AU - Al-Ghadhban, Amer

AU - Dang, Shuping

AU - Shihada, Basem

N1 - KAUST Repository Item: Exported on 2020-12-28

PY - 2020

Y1 - 2020

N2 - Management of network becomes increasingly difficult due to the rapid proliferation of the Internet of Things (IoT) and heterogeneous demands of applications. To mitigate congestion and maintain a high quality of service (QoS) for application users, we propose an importance-oriented clustering-based QoS system named ICAQ. The system uses unsupervised machine learning to determine and differentiate different application flow priority. The system is proposed to be a generic to both network core features and the application features. An environment monitoring IoT application is implemented as an example to demonstrate the expressive power of ICAQ. Experimental results have verified the effectiveness and efficiency of ICAQ and show a promising potential for using ICAQ for the QoS management of IoT applications in 5G and beyond networks.

AB - Management of network becomes increasingly difficult due to the rapid proliferation of the Internet of Things (IoT) and heterogeneous demands of applications. To mitigate congestion and maintain a high quality of service (QoS) for application users, we propose an importance-oriented clustering-based QoS system named ICAQ. The system uses unsupervised machine learning to determine and differentiate different application flow priority. The system is proposed to be a generic to both network core features and the application features. An environment monitoring IoT application is implemented as an example to demonstrate the expressive power of ICAQ. Experimental results have verified the effectiveness and efficiency of ICAQ and show a promising potential for using ICAQ for the QoS management of IoT applications in 5G and beyond networks.

UR - http://hdl.handle.net/10754/666661

UR - https://ieeexplore.ieee.org/document/9295652/

U2 - 10.1109/ICCT50939.2020.9295652

DO - 10.1109/ICCT50939.2020.9295652

M3 - Conference contribution

SN - 978-1-7281-8142-4

BT - 2020 IEEE 20th International Conference on Communication Technology (ICCT)

PB - IEEE

ER -

ICAQ: Adaptive QoS System for 5G and Beyond Applications

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