Journal of KIISE:Databases (한국정보과학회논문지:데이타베이스)

Korean Institute of Information Scientists and Engineers (한국정보과학회)
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Processing Sliding Windows over Disordered Streams

비순서화된 스트림 처리를 위한 슬라이딩 윈도우 기법

  • 김현규 (한국과학기술원 전산학과) ;
  • 김철기 (한국정보통신대학교 모바일 멀티미디어연구소) ;
  • 김명호 (한국과학기술원 전산학과)
  • Published : 2006.11.15
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Abstract

Disordered streams cause two issues in processing sliding windows: i) how to place input tuples into a buffer in an increasing order efficiently and ii) how to determine a time point to process the windows from input tuples in the buffer. To address these issues, we propose a structure and method of operators for processing sliding windows. We first present a structure of the operators using an index to handle input tuples efficiently. Then, we propose a method to determine the time point to process the windows, which is called a mean-based estimation. In the proposed method, users can describe parameters required for estimation in a query specification, which provides a way for users to control the properties of query results such as the accuracy or the response time according to application requirements. Our experimental results show that the mean-based estimation provides better adaptivity and stability than the one used in the existing method.

비순서화된 스트림은 슬라이딩 윈도우의 생성에 있어서 두 가지 문제점을 야기한다. 첫째는 스트림을 효율적으로 정렬하는 문제이며, 둘째는 정렬된 스트림으로부터 윈도우를 언제 생성할지 결정하는 문제이다. 본 논문에서는 이러한 문제를 해결하기 위한 윈도우 오퍼레이터의 구조와 방법에 대해 제안한다. 먼저 입력 튜플을 효율적으로 정렬하고 저장하기 위해 인덱스를 이용한 오퍼레이터의 구조를 소개한다. 그리고 윈도우의 생성 시점을 결정하기 위한 평균-기반 추정 방식을 제안한다. 제안하는 기법에서는 추정에 필요한 매개변수를 질외문에서 정의할 수 있으며, 이를 통해 사용자가 어플리케이션의 요구사항에 따라 정확성이나 응답 시간과 같은 질의 결과의 특성을 조절할 수 있도록 지원한다. 본 논문의 실험 결과는 제안한 평균-기반 방식이 기존의 연구에서 이용한 방식보다 적응성과 안정성이 우수하다는 것을 보인다.

Keywords

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