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Cloud-Assisted Real-Time transrating for http live streaming

Cloud-Assisted Real-Time transrating for http live streaming. Speaker ： 梁景棠 Advisor ： 許子衡 Class ： 碩資工一甲 Student ID ： MA2G0107 Author ： Chin- Feng Lai Han- Chieh Chao Published ： 2013. Outline. Introduction Research Methods Results Conclusion. Introduction.

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Cloud-Assisted Real-Time transrating for http live streaming

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  1. Cloud-Assisted Real-Time transrating for http live streaming Speaker ：梁景棠 Advisor：許子衡 Class：碩資工一甲 Student ID：MA2G0107 Author ：Chin-Feng Lai Han-Chieh Chao Published：2013

  2. Outline • Introduction • Research Methods • Results • Conclusion

  3. Introduction • The public have gradually changed from viewing offline medias to viewing medias using network streaming on personal computers or hand-held devices • The existing multimedia streaming technologies can be approximately divided into: • Push streaming mode • Request streaming mode

  4. Research Methods • Cloud-ssisted Real-Time adaptive transcoding system

  5. Research Methods • Normal Mode: • Active Mode: • Conservative Mode:

  6. Research Methods • Transrating state machine

  7. Research Methods • Finally, in the operational flow of the server transcoding, when the client sends a request to the server to download media segments, the segment start is entered. • In the download period of the client, the server continuously records the size of each packet and transmission time. • When the download is completed, the server immediately calculates the average download bit rate of current media segment, and compares it with the average download bit rate of the previous media segment to obtain an error; at this moment, the mode transition state machine determines the mode, and dynamically generates the estimated bit rate value of the next media segment according to the transcoding strategy corresponding to each state.

  8. Results • Bitrate to segment for scenario

  9. Results • Bandwidth usage comparison for scenario

  10. Results • Analysis of PSNR for scenario

  11. Results • PSNR comparison for scenario

  12. Conclusion • This article designs a cloud-assisted real-time transrating mechanism based on HLS protocol • Implements the bandwidth recoder, segment transrater, and segment rediretor on the server, instantly analyzes the on-line quality between client and server without changing the HLS server architecture • Provides the optimum media quality, in order that the client leads the HTTP requirement in the transrated media segment using HTTP redirection technology.

  13. Conclusion • Multimedia segments can be dispersed in different servers in the future, or can construct cloud access systems among HLS servers, even among network domains, in order to reduce the probable load on a single server or a single network domain, thus, increasing the overall bandwidth utilization rate and improving media quality for global users.

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