Q-FDBA : improving QoE fairness for video streaming.

Jiang, Jingyan and Hu, Liang and Hao, Pingting and Sun, Rui and Hu, Jiejun and Li, Hongtu (2018) Q-FDBA : improving QoE fairness for video streaming. Multimedia Tools and Applications, 77 (9). pp. 10787-10806. ISSN 1380-7501

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Multiplayer video streaming scenario can be seen everywhere today as the video traffic is becoming the “killer” traffic over the Internet. The Quality of Experience fairness is critical for not only the users but also the content providers and ISP. Consequently, a QoE fairness adaptive method of multiplayer video streaming is of great importance. Previous studies focus on client-side solutions without network global view or network-assisted solution with extra reaction to client. In this paper, a pure network-based architecture using SDN is designed for monitoring network global performance information. With the flexible programming and network mastery capacity of SDN, we propose an online Q-learning-based dynamic bandwidth allocation algorithm Q-FDBA with the goal of QoE fairness. The results show the Q-FDBA could adaptively react to high frequency of bottleneck bandwidth switches and achieve better QoE fairness within a certain time dimension.

Item Type:
Journal Article
Journal or Publication Title:
Multimedia Tools and Applications
Uncontrolled Keywords:
?? hardware and architecturemedia technologysoftwarecomputer networks and communications ??
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Deposited On:
20 Jul 2023 15:35
Last Modified:
28 Nov 2023 10:37