초록

캐싱은 데이타 방송 시스템에서 방송 요청의 경쟁을 줄임으로써 좁은 대역폭으로 인한 시스템 성능의 저하를 완화할 수 있는 유용한 방법이다. 본 논문에서는, 풀 기반 방송 시스템에서 클라이언트들간의 데이타 인기도를 반영하는 캐싱 전략을 제안한다. 아울러, 데이타 방송 버전을 이용하여 데이타 접근의 최근성을 반영할 수 있도록 하고 제안한 전략의 성능을 시뮬레이션을 통하여 평가한다. 성능 평가에 따르면, 히트율과 미스 비용을 함께 고려한 전략이 전통적 전략인 LRU 보다 성능 우위를 보이고 있다. 클라이언트들의 데이타 인기도를 고려한 전략은 일부 경우에 있어 성능 우위를 보여 주고 있다.

Abstract

A caching is a useful technique to alleviate performance degradation due to the inherent narrow bandwidth by reducing contention of broadcast requests. In this paper, we propose a caching strategy for pull-based data broadcast system which considers data popularity among clients. In addition, the proposed strategy also reflects recentness of data access based on data broadcast version. Then, we evaluate the performance of proposed strategy through a simulation approach. According to the results, the strategy considering both hit ratio and miss cost shows better performance than the traditional LRU. In addition, the strategy considering data popularity among clients shows better performance in some cases.

주제어

#데이타 방송   #캐싱   #데이타 인기도  

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