QoE-Driven Dynamic Adaptive Video Streaming Strategy With Future Information
Research output: Contribution to journal › Article › Scientific › peer-review
|Number of pages||12|
|Journal||IEEE Transactions on Broadcasting|
|Publication status||Published - Sep 2017|
|Publication type||A1 Journal article-refereed|
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.