Conference proceeding
QoS Guaranteed Resource Allocation for Coexisting eMBB and URLLC Traffic in 5G Industrial Networks
2022 IEEE 28th International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA), pp.81-90
08/2022
DOI: 10.1109/RTCSA55878.2022.00015
Abstract
The fifth-generation (5G) cellular networks are increasingly considered for industrial applications, such as factory automation systems. In 5G networks, Enhanced Mobile Broadband (eMBB) and Ultra-Reliable Low-Latency Communication (URLLC) are two essential services. eMBB services require high data rates with some lower bounds while URLLC traffic is subject to strict latency and reliability requirements. Existing approaches to scheduling coexisting eMBB and URLLC traffic all assume that URLLC traffic preempts eMBB traffic immediately upon arrival, which can adversely impact the achievable eMBB data rates. Furthermore, none of the prior work considers guaranteeing minimum data rate requirements imposed on certain eMBB traffic. This paper proposes a new model to capture the URLLC and eMBB requirements and introduces a novel framework, QoSG-RA, to perform network resource allocation for coexisting eMBB and URLLC traffic. QoSG-RA builds on a hybrid offline/online approach which performs offline resource allocation to ensure the Quality of Service (QoS) requirements of eMBB and URLLC traffic to be satisfied and online resource allocation to maximize fairness on the data rates among eMBB traffic based on runtime information. QoSG-RA is able to (i) meet latency and reliability requirements of URLLC traffic, and (ii) maximize the data rates for eMBB traffic in a fair way while fulfilling their minimum data rate requirements. Experimental results demonstrate the effectiveness of QoSG-RA compared to the state-of-the-art.
Details
- Title: Subtitle
- QoS Guaranteed Resource Allocation for Coexisting eMBB and URLLC Traffic in 5G Industrial Networks
- Creators
- Dawei Shen - Northeastern UniversityTianyu Zhang - Northeastern UniversityJiachen Wang - University of ConnecticutQingxu Deng - Northeastern UniversitySong Han - University of ConnecticutXiaobo Sharon Hu - University of Notre Dame
- Resource Type
- Conference proceeding
- Publication Details
- 2022 IEEE 28th International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA), pp.81-90
- Publisher
- IEEE
- DOI
- 10.1109/RTCSA55878.2022.00015
- ISSN
- 1533-2306
- eISSN
- 2325-1301
- Grant note
- Technology Development (10.13039/100006180) Liaoning Revitalization Talents Program (10.13039/501100018617)
- Language
- English
- Date published
- 08/2022
- Academic Unit
- Computer Science
- Record Identifier
- 9984696723102771
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