A. N. Abbou, T. Taleb and J. Song, "A Software-Defined Queuing Framework for QoS Provisioning in 5G and Beyond Mobile Systems," in IEEE Network, vol. 35, no. 2, pp. 168-173, March/April 2021, doi: 10.1109/MNET.011.2000441
A software-defined queuing framework for QoS provisioning in 5G and beyond mobile systems
|Author:||Abbou, Aiman Nait1; Taleb, Tarik1,2,3; Song, JaeSeung2|
1Aalto University, Espoo, Finland
2Sejong University, Seoul, South Korea
3University of Oulu, Oulu, Finland
|Online Access:||PDF Full Text (PDF, 2.2 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2021052631655
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2021-05-26
There is an ever-increasing demand for network technologies supporting Ultra-Reliable Low Latency Communications (URLLC) services and their co-existence with best-effort traffic. By way of example, reference can be made to the emerging 5G mobile networks. In this vein, this article investigates the Software-Defined Networking (SDN) technology capabilities for providing Quality of Service (QoS) guarantees. Specifically, we present a testbed, under development, dubbed Soft-ware-Defined Queueing (SDQ). This framework leverages QoS provision functionalities of SDN. SDQ can be regarded as a framework for testing traffic engineering solutions in networks with deterministic QoS support. By using SDQ, we develop and test a specific solution that chooses the optimal queue and path for each incoming flow in order to reduce the workload imbalances in the network. For the experimental setup, we consider a generic SDN network whose bridges include three priority queues at every output port. Furthermore, we compare the aforementioned solution with a best-effort network and an SDN-enabled network with QoS support configured by default. The obtained results show that the envisioned solution outperforms the baseline one of SDN and the best-effort solution in terms of the average latency recorded.
|Pages:||168 - 173|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This work was partially supported by the European Union's Horizon 2020 Research and Innovation Program through the MonB5G Project under Grant No. 871780. It was also supported in part by the Academy of Finland 6Genesis project under Grant No. 318927 and by the Academy of Finland CSN project under Grant No. 311654. Prof. Song was supported by the Korea Research Foundation with funding from the Ministry of Science, Technology, Information and Communication under Grant No. 2018-0-88457.
|Academy of Finland Grant Number:||
318927 (Academy of Finland Funding decision)
311654 (Academy of Finland Funding decision)
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