Journal of KIISE:Computer Systems and Theory (한국정보과학회논문지:시스템및이론)

Korean Institute of Information Scientists and Engineers (한국정보과학회)
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Block Level Refinement of Popularity-Aware Interval Caching for Multimedia Streaming Servers

멀티미디어 스트리밍 서버를 위한 인기도 기반 인터벌 캐슁의 블록 수준 세분화 기법

  • 권오훈 (서울대학교 컴퓨터공학과) ;
  • 김태석 (서울대학교 컴퓨터공학과) ;
  • 반효경 (이화여자대학교 컴퓨터공학과) ;
  • 고건 (서울대학교 컴퓨터공학과)
  • Published : 2007.04.15
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Abstract

With recent proliferation of video-on-demand services, caching in a multimedia streaming server is becoming increasingly important. Previous studies have shown that request interval based caching and its extension for considering different video popularity performs well in various streaming environments. In this paper, we show that block level refinement of this existing scheme can further improve the performance of streaming servers. Trace driven simulations with real world VOD traces have shown that the proposed scheme improves the cache hit rate and the startup latency.

최근 VOD(Video-On-Demand) 서비스가 널리 이용되면서 멀티미디어 스트리밍 서버를 위한 데이타 캐슁 기법의 중요성이 점점 증가하고 있다. 기존 연구를 통해 인터벌 캐슁 기법과 이를 객체의 인기도를 반영하도록 확장한 기법들이 다양한 환경에서 우수한 성능을 나타냄이 입증되었다. 본 논문에서는 이와 같은 기존의 기법을 블록 수준으로 세분화할 경우 멀티미디어 스트리밍 서버의 성능을 더욱 향상 시킬 수 있음을 보인다. 실제 VOD 서버의 트레이스를 이용한 시뮬레이션 실험을 통해 본 논문이 제안한 알고리즘이 캐쉬 적중률과 스트림의 초기 지연 시간을 향상시킴을 보인다.

Keywords

References

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