Server-efficient high-definition media dissemination

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Server-efficient high-definition media dissemination

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International Workshop on Network and Operating System Support for Digital Audio and Video archive
Proceedings of the 18th international workshop on Network and operating systems support for digital audio and video table of contents

Williamsburg, VA, USA

SESSION: OS and end-systems table of contents

Pages 49-54

Year of Publication: 2009

ISBN:978-1-60558-433-1

Authors

Philip W. Frey	IBM Research GmbH, Rueschlikon, Switzerland
Andreas Hasler	IBM Research GmbH, Rueschlikon, Switzerland
Bernard Metzler	IBM Research GmbH, Rueschlikon, Switzerland
Gustavo Alonso	ETH, Zurich, Switzerland

Sponsors

SIGCOMM: ACM Special Interest Group on Data Communication
SIGMULTIMEDIA: ACM Special Interest Group on Multimedia
ACM: Association for Computing Machinery

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ACM New York, NY, USA

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ABSTRACT

Internet usage has changed dramatically in the past few years. Content is no longer dominated by static websites, but comprises an increasing number of multimedia streams. With the widespread availability of broadband connections, the quality of the media provided by video-on-demand as well as streaming services increases constantly. Even though today most videos are still encoded with a rather low bit rate, large Internet service providers already foresee high-definition media becoming the predominant format in the near future. However, a larger number of clients requesting media at high bit rates poses a challenge for the server infrastructure. Conventional stream dissemination methods, such as RTP over UDP or HTTP over TCP, result in high server loads due to excessive local data copy, context switching, and interrupt processing overhead. In this paper, we illustrate and discuss this problem in detail through extensive experiments with existing solutions. We then present a new approach based on zero-copy protocol stack implementations in software as well as dedicated RDMA hardware. Our performance experiments indicate that these optimizations allow servers to scale better and remove most of the overhead caused by current approaches.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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