TY - JOUR
T1 - QoE-Driven dynamic adaptive video streaming strategy with future information
AU - Yu, Li
AU - Tillo, Tammam
AU - Xiao, Jimin
N1 - Publisher Copyright:
© 1963-12012 IEEE.
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 - QoE
KW - on-demand video streaming
KW - variable bitrate streaming
UR - http://www.scopus.com/inward/record.url?scp=85018483051&partnerID=8YFLogxK
U2 - 10.1109/TBC.2017.2687698
DO - 10.1109/TBC.2017.2687698
M3 - Article
AN - SCOPUS:85018483051
SN - 0018-9316
VL - 63
SP - 523
EP - 534
JO - IEEE Transactions on Broadcasting
JF - IEEE Transactions on Broadcasting
IS - 3
M1 - 7898405
ER -