Research output per year
Research output per year
Research output: Contribution to journal › Article › peer-review
Existing desktop virtualization systems suffer from a very limited performance in replaying high-definition videos remotely: intolerable CPU and bandwidth consumption, high response delay and poor video quality. In this paper, we propose an original-stream based solution to provide good user experience for replaying high-definition videos in desktop virtualization systems without any modification on applications and support most of prevalent high-definition video formats. In our solution, server's video content is not decoded on server but intercepted and delivered to client in its originally encoded state, so that the video content can be easily stored and transported in computer systems with high quality and low bandwidth. The encoded video content is intercepted in server's display driver, which enables HDR to work seamlessly with existing applications. The extremely CPU-intensive video decoding tasks are executed on client by using GPU-accelerated video decoding technology so that CPU can concentrate on other tasks. The experimental results validate our method and show that this proposed approach measurably outperforms state-of-the-art solutions.
| Original language | English |
|---|---|
| Pages (from-to) | 676-683 |
| Number of pages | 8 |
| Journal | Journal of Visual Languages and Computing |
| Volume | 25 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 2014 |
| Externally published | Yes |
Research output: Chapter in Book/Conference paper › Conference paper › peer-review