Abstract
With the rapid development of cellular networks, demand for real-time stream is increasing dramatically. How to guarantee better quality-of-service (QoS) of real-time stream services under limited resources becomes an increasingly important issue. This paper proposes a delay based hierarchical downlink scheduling (DBS) algorithm for real-time stream in cellular networks. The hierarchical scheduler is divided into two levels. The upper level scheduler offers a prediction of the number of data bits that each real-time stream needs to guarantee the QoS. The lower level scheduler classifies all real-time streams into grade A, B and C according to Head of Line Delay and allocates resources to streams according to their different grades. The simulation results show that our algorithm performs better than other real-time schedulers, such as frame level scheduler (FLS), Modified Largest Weight Delay First (M-LWDF), EXP/PF and EXP-LOG in the aspects of delay and throughput.
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Acknowledgment
This work has been sponsored by National Engineering Laboratory for Next Generation Internet Technologies open fund project, Research on network traffic prediction technology based on spatiotemporal deep learning model, National Science Foundation of China (No. 61201149) and Huawei Research Fund (grant No. YBN2016110032). The authors would also like to thank the reviewers for their constructive comments.
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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Fan, W., Liu, Y., Wang, Y. (2020). DBS: Delay Based Hierarchical Downlink Scheduling for Real-Time Stream in Cellular Networks. In: Gao, H., Feng, Z., Yu, J., Wu, J. (eds) Communications and Networking. ChinaCom 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 312. Springer, Cham. https://doi.org/10.1007/978-3-030-41114-5_19
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DOI: https://doi.org/10.1007/978-3-030-41114-5_19
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