TUTCRIS - Tampereen teknillinen yliopisto

TUTCRIS

QoE-Driven Dynamic Adaptive Video Streaming Strategy With Future Information

Tutkimustuotosvertaisarvioitu

Standard

QoE-Driven Dynamic Adaptive Video Streaming Strategy With Future Information. / Yu, Li; Tillo, Tammam; Xiao, Jimin.

julkaisussa: IEEE Transactions on Broadcasting, Vuosikerta 63, Nro 3, 09.2017, s. 523-534.

Tutkimustuotosvertaisarvioitu

Harvard

Yu, L, Tillo, T & Xiao, J 2017, 'QoE-Driven Dynamic Adaptive Video Streaming Strategy With Future Information', IEEE Transactions on Broadcasting, Vuosikerta. 63, Nro 3, Sivut 523-534. https://doi.org/10.1109/TBC.2017.2687698

APA

Yu, L., Tillo, T., & Xiao, J. (2017). QoE-Driven Dynamic Adaptive Video Streaming Strategy With Future Information. IEEE Transactions on Broadcasting, 63(3), 523-534. https://doi.org/10.1109/TBC.2017.2687698

Vancouver

Yu L, Tillo T, Xiao J. QoE-Driven Dynamic Adaptive Video Streaming Strategy With Future Information. IEEE Transactions on Broadcasting. 2017 syys;63(3):523-534. https://doi.org/10.1109/TBC.2017.2687698

Author

Yu, Li ; Tillo, Tammam ; Xiao, Jimin. / QoE-Driven Dynamic Adaptive Video Streaming Strategy With Future Information. Julkaisussa: IEEE Transactions on Broadcasting. 2017 ; Vuosikerta 63, Nro 3. Sivut 523-534.

Bibtex - Lataa

@article{9b1426b0796d4d0ea537a6b2914c1234,
title = "QoE-Driven Dynamic Adaptive Video Streaming Strategy With Future Information",
abstract = "DASH, the Dynamic adaptive video streaming over hypertext transfer protocol (HTTP), has become the de-facto video delivery mechanism nowadays, which takes advantage of the existing low cost and wide-spread HTTP platforms. Standards like MPEG-DASH defines the bitstreams conformance and decoding process, while leaving the bitrate adaptive algorithm open for research. So far, most DASH researches focus on the constant bitrate video delivery. In this paper, various bitrate (VBR) video delivery is investigated in the on-demand streaming scenario. Detailed instant bitrates of future segments are exploited in the proposed adaptation method to grasp the fluctuation traits of the VBR video. Meanwhile, the adaptation problem is formulated as an optimization process with the proposed internal QoE goal function, which keeps a good balance between various requirements. Besides, the parameters within the internal QoE function can be tuned to guarantee the flexibility of meeting different preferences. The experimental results demonstrate that our proposed QoE-based video adaptation method outperforms the state-of-the-art method with a good margin.",
keywords = "DASH, variable bitrate streaming, QoE, on-demand video streaming, HTTP, ALGORITHM, NETWORKS, CHANNELS",
author = "Li Yu and Tammam Tillo and Jimin Xiao",
year = "2017",
month = "9",
doi = "10.1109/TBC.2017.2687698",
language = "English",
volume = "63",
pages = "523--534",
journal = "IEEE Transactions on Broadcasting",
issn = "0018-9316",
publisher = "IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC",
number = "3",

}

RIS (suitable for import to EndNote) - Lataa

TY - JOUR

T1 - QoE-Driven Dynamic Adaptive Video Streaming Strategy With Future Information

AU - Yu, Li

AU - Tillo, Tammam

AU - Xiao, Jimin

PY - 2017/9

Y1 - 2017/9

N2 - DASH, the Dynamic adaptive video streaming over hypertext transfer protocol (HTTP), has become the de-facto video delivery mechanism nowadays, which takes advantage of the existing low cost and wide-spread HTTP platforms. Standards like MPEG-DASH defines the bitstreams conformance and decoding process, while leaving the bitrate adaptive algorithm open for research. So far, most DASH researches focus on the constant bitrate video delivery. In this paper, various bitrate (VBR) video delivery is investigated in the on-demand streaming scenario. Detailed instant bitrates of future segments are exploited in the proposed adaptation method to grasp the fluctuation traits of the VBR video. Meanwhile, the adaptation problem is formulated as an optimization process with the proposed internal QoE goal function, which keeps a good balance between various requirements. Besides, the parameters within the internal QoE function can be tuned to guarantee the flexibility of meeting different preferences. The experimental results demonstrate that our proposed QoE-based video adaptation method outperforms the state-of-the-art method with a good margin.

AB - DASH, the Dynamic adaptive video streaming over hypertext transfer protocol (HTTP), has become the de-facto video delivery mechanism nowadays, which takes advantage of the existing low cost and wide-spread HTTP platforms. Standards like MPEG-DASH defines the bitstreams conformance and decoding process, while leaving the bitrate adaptive algorithm open for research. So far, most DASH researches focus on the constant bitrate video delivery. In this paper, various bitrate (VBR) video delivery is investigated in the on-demand streaming scenario. Detailed instant bitrates of future segments are exploited in the proposed adaptation method to grasp the fluctuation traits of the VBR video. Meanwhile, the adaptation problem is formulated as an optimization process with the proposed internal QoE goal function, which keeps a good balance between various requirements. Besides, the parameters within the internal QoE function can be tuned to guarantee the flexibility of meeting different preferences. The experimental results demonstrate that our proposed QoE-based video adaptation method outperforms the state-of-the-art method with a good margin.

KW - DASH

KW - variable bitrate streaming

KW - QoE

KW - on-demand video streaming

KW - HTTP

KW - ALGORITHM

KW - NETWORKS

KW - CHANNELS

U2 - 10.1109/TBC.2017.2687698

DO - 10.1109/TBC.2017.2687698

M3 - Article

VL - 63

SP - 523

EP - 534

JO - IEEE Transactions on Broadcasting

JF - IEEE Transactions on Broadcasting

SN - 0018-9316

IS - 3

ER -