Traffic-based Caching Algorithm and Performance Evaluation for QoS-adaptive Streaming Proxy Server in Wireless Networks

무선 환경에서 QoS 적응적인 스트리밍 프락시 서버를 위한 트래픽 기반 캐싱 알고리즘 및 성능 분석

  • Kim, HwaSung (Dept. Electronic and Communications Engineering, Kwang Woon Univ) ;
  • Kim, YongSul (Dept. Electronic and Communications Engineering, Kwang Woon Univ) ;
  • Hong, JungPyo (LG Electronics DM Research Institute)
  • 김화성 (광운대학교 전자통신공학과) ;
  • 김용술 (광운대학교 전자통신공학과) ;
  • 홍정표 (LG 전자 DM 연구소)
  • Published : 2005.09.01

Abstract

The increasing popularity of multimedia streaming services introduces new challenges in content distribution. Especially, it is important to provide the QoS guarantees as they are increasingly expected to support the multimedia applications. Multimedia streams typically experience the high start-up delay due to the large protocol overhead, the delay, and the loss properties of the wireless networks. The service providers can improve the performance of multimedia streaming by caching the initial segment (prefix) of the popular streams at proxies near the requesting clients. The proxy can initiate transmission to the client while requesting the remainder of the stream from the server. In this paper, we propose the traffic based caching algorithm (TSLRU) to improve the performance of caching proxy. TSLRU classifies the traffic into three types, and improve the performance of caching proxy by reflecting the several elements such as traffic types, recency, frequency, object size when performing the replacement decision. In simulation, TSLRU performs better than the existing schemes in terms of byte hit rate, hit rate, startup latency, and throughput.

멀티미디어 스트리밍 서비스의 증가는 인터넷 컨텐츠의 새로운 국면으로 나타나고 있다. 특히, 무선이동통신망에서 증가하는 멀티미디어 응용에 대한 QoS 제공은 무엇보다 중요하다. 멀티미디어 스트림은 일반적으로 인터넷과 무선망의 유실 특성, 지연, 프로토콜 오버헤드로 인해 높은 초기 지연시간을 가진다. 서비스 제공자는 클라이언트 가까이에 있는 프락시에서 자주 액세스 되어지는 멀티미디어 스트림의 초기 세그먼트를 캐슁함으로써 성능을 향상 시킬 수 있다. 프락시는 서버로부터 스트림의 나머지 부분을 요구함과 동시에 클라이언트에 전송을 시작할 수 있다. 본 논문에서는 캐슁 프락시의 성능을 향상시키기 위해 트래픽 기반 캐슁 기법(TSLRU)을 제안한다 TSLRU는 트래픽을 세 종류로 분류하여 캐슁하며, 교체 대상 결정 시 여러 요소(traffic types, recency, frequency, object size)를 반영함으로 써 캐슁 프락시의 성능을 향상 시킨다. 모의실험에서 캐슁 알고리즘은 byte hit rate과 startup latency에서 높은 성능을 보였다.

Keywords

References

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