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A QoE adaptive management system for high definition video streaming over wireless networks

Author

Listed:
  • Miran Taha

    (Integrated Management Coastal Research Institute, Universitat Politécnica de Valencia
    University of Sulaimani)

  • Alejandro Canovas

    (Integrated Management Coastal Research Institute, Universitat Politécnica de Valencia)

  • Jaime Lloret

    (Integrated Management Coastal Research Institute, Universitat Politécnica de Valencia)

  • Aree Ali

    (University of Sulaimani
    University of Halabja)

Abstract

The development of the smart devices had led to demanding high-quality streaming videos over wireless communications. In Multimedia technology, the Ultra-High Definition (UHD) video quality has an important role due to the smart devices that are capable of capturing and processing high-quality video content. Since delivery of the high-quality video stream over the wireless networks adds challenges to the end-users, the network behaviors ‘factors such as delay of arriving packets, delay variation between packets, and packet loss, are impacted on the Quality of Experience (QoE). Moreover, the characteristics of the video and the devices are other impacts, which influenced by the QoE. In this research work, the influence of the involved parameters is studied based on characteristics of the video, wireless channel capacity, and receivers’ aspects, which collapse the QoE. Then, the impact of the aforementioned parameters on both subjective and objective QoE is studied. A smart algorithm for video stream services is proposed to optimize assessing and managing the QoE of clients (end-users). The proposed algorithm includes two approaches: first, using the machine-learning model to predict QoE. Second, according to the QoE prediction, the algorithm manages the video quality of the end-users by offering better video quality. As a result, the proposed algorithm which based on the least absolute shrinkage and selection operator (LASSO) regression is outperformed previously proposed methods for predicting and managing QoE of streaming video over wireless networks.

Suggested Citation

  • Miran Taha & Alejandro Canovas & Jaime Lloret & Aree Ali, 2021. "A QoE adaptive management system for high definition video streaming over wireless networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 77(1), pages 63-81, May.
    • Handle: RePEc:spr:telsys:v:77:y:2021:i:1:d:10.1007_s11235-020-00741-2
    DOI: 10.1007/s11235-020-00741-2
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    References listed on IDEAS

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    1. Jaroslav Frnda & Miroslav Voznak & Lukas Sevcik, 2016. "Impact of packet loss and delay variation on the quality of real-time video streaming," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 62(2), pages 265-275, June.
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    Cited by:

    1. Megha Sahu & Sri Pramodh Rachuri & Ahtisham Ali Ansari & Arzad Alam Kherani, 2022. "Traffic splitting for delay jitter control in multi-access systems," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 80(4), pages 513-527, August.

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