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A Demand Adaptive and Locality Aware (DALA) streaming media server cluster architecture
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Source International Workshop on Network and Operating System Support for Digital Audio and Video archive
Proceedings of the 12th international workshop on Network and operating systems support for digital audio and video table of contents
Miami, Florida, USA
SESSION: Video Streaming 1 table of contents
Pages: 139 - 146  
Year of Publication: 2002
ISBN:1-58113-512-2
Authors
Zihui Ge  University of Massachusetts, Amherst, MA
Ping Ji  University of Massachusetts, Amherst, MA
Prashant Shenoy  University of Massachusetts, Amherst, MA
Sponsors
ACM: Association for Computing Machinery
SIGMULTIMEDIA: ACM Special Interest Group on Multimedia
Publisher
ACM  New York, NY, USA
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ABSTRACT

The wide availability of broadband networking technologies such as cable modems and DSL coupled with the growing popularity of the Internet has led to a dramatic increase in the availability and the use of online streaming media. With the "last mile" network bandwidth no longer a constraint, the bottleneck for video streaming has been pushed closer to the server. Streaming high quality audio and video to a myriad of clients imposes significant resource demands on the server. In this work, we propose a demand adaptive and locality aware (DALA) clustered media server architecture that can dynamically allocate resources to adapt to changing demand and also maximize the number of clients serviced by the server cluster. Moreover, our design exploits temporal locality among requests by dispatching newly arriving requests to servers that are already servicing prior requests for those objects, thereby extracting the benefits of locality. We explore the efficacy of the DALA clustered architecture using simulations. Our simulation results show that DALA is highly adaptive, exhibits significant performance gains when compared to static schemes, and has a low system overhead. Our results demonstrate that DALA is a simple, yet effective approach for designing clustered media servers.


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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Collaborative Colleagues:
Zihui Ge: colleagues
Ping Ji: colleagues
Prashant Shenoy: colleagues