KIPS Transactions on Software and Data Engineering (정보처리학회논문지:소프트웨어 및 데이터공학)

Korea Information Processing Society (한국정보처리학회)
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A Cost-Efficient Job Scheduling Algorithm in Cloud Resource Broker with Scalable VM Allocation Scheme

클라우드 자원 브로커에서 확장성 있는 가상 머신 할당 기법을 이용한 비용 적응형 작업 스케쥴링 알고리즘

  • ;
  • 김성환 (한국과학기술원 전기및전자공학과) ;
  • 강동기 (한국과학기술원 전기및전자공학과) ;
  • 김병상 (한국과학기술원 정보통신공학과) ;
  • 윤찬현 (한국과학기술원 전기및전자공학과)
  • Received : 2012.11.22
  • Accepted : 2012.12.03
  • Published : 2012.12.31
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Abstract

Cloud service users request dedicated virtual computing resource from the cloud service provider to process jobs in independent environment from other users. To optimize this process with automated method, in this paper we proposed a framework for workflow scheduling in the cloud environment, in which the core component is the middleware called broker mediating the interaction between users and cloud service providers. To process jobs in on-demand and virtualized resources from cloud service providers, many papers propose scheduling algorithms that allocate jobs to virtual machines which are dedicated to one machine one job. With this method, the isolation of being processed jobs is guaranteed, but we can't use each resource to its fullest computing capacity with high efficiency in resource utilization. This paper therefore proposed a cost-efficient job scheduling algorithm which maximizes the utilization of managed resources with increasing the degree of multiprogramming to reduce the number of needed virtual machines; consequently we can save the cost for processing requests. We also consider the performance degradation in proposed scheme with thrashing and context switching. By evaluating the experimental results, we have shown that the proposed scheme has better cost-performance feature compared to an existing scheme.

사용자들은 자신의 작업을 처리하기 위해 자신에게만 한정된 가상 컴퓨팅 자원을 클라우드 서비스 제공자로부터 할당 받아 타 사용자로부터 독립된 환경에서 작업을 처리하게 된다. 이를 자동화된 방법으로 최적화를 대신 수행해주기 위한 모델로 브로커 미들웨어가 제시되었고 마감시간을 만족하는 이내에서 자원 이용률을 높이는 접근법으로 필요 가상 머신의 숫자를 줄여 비용을 절약한다. 이를 다루는 많은 논문들에서 작업 스케줄링은 기존 사용자들간의 독립을 보장하여 하나의 가상 머신이 하나의 작업에 한정된 가상 머신에서 처리하는 방식으로 다루어지고 있다. 하지만 기존의 SRSV 방식에서는 높은 정도의 다중 프로그래밍 작업이 아닐 경우 시스템을 효율적으로 사용하지 못한다. 이에 본 논문에서는 해당 자원을 마감시간과 스래싱(thrashing), 문맥 전환(context switching)에 따른 성능 저하를 고려한 상태에서 다중 프로그래밍 정도를 높여 낭비되는 자원을 최소화하여 비용을 절약하려고 한다. 실험 결과를 통해 제안하는 방법이 제약조건 이내에서 기존의 방식에 비해 좀 더 좋은 가격 대비 성능을 가지는 것을 보인다.

Keywords

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