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http://dx.doi.org/10.9723/jksiis.2010.15.4.017

ECPS: Efficient Cloud Processing Scheme for Massive Contents  

Na, Moon-Sung (단국대학교 정보컴퓨터공학과)
Kim, Seung-Hoon (단국대학교 멀티미디어공학과)
Lee, Jae-Dong (단국대학교 컴퓨터학부)
Publication Information
Journal of Korea Society of Industrial Information Systems / v.15, no.4, 2010 , pp. 17-27 More about this Journal
Abstract
Major IT vendors expect that cloud computing technology makes it possible to reduce the contents service cycle, speed up application deployment and skip the installation process, reducing operational costs, proactive management etc. However, cloud computing environment for massive content service solutions requires high-performance data processing to reduce the time of data processing and analysis. In this study, Efficient_Cloud_Processing_Scheme(ECPS) is proposed for allocation of resources for massive content services. For high-performance services, optimized resource allocation plan is presented using MapReduce programming techniques and association rules that is used to detect hidden patterns in data mining, based on levels of Hadoop platform(Infrastructure as a service). The proposed ECPS has brought more than 20% improvement in performance and speed compared to the traditional methods.
Keywords
Cloud Computing; Resource Allocation; Massive Contents;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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1 Lamine M. Aouad, Nhien-An Le-Khac, and Tahar M. Kechadi. "Distributed frequent itemsets mining in heterogeneous platforms," Engineering, Computing and Archtecture, 1, 2007.
2 이미영, "클라우드 기반 대규모 데이터 처리 및 관리 기술," 전자통신동향분석 제24권 제4호, 한국전자통신연구원, 2009.
3 Park Yong Kwang, "A Study on Developmental Direction of the Cloud Computing," Master's thesis, HanYang University, 2009.
4 J. Boulon, A. Konwinski, R. Qi, A. Rabkin, E. Yang, and M. Yang. Chukwa: "A Large-scale Monitoring System," In Cloud Computing and Its Applications, Chicago, IL, Oct 2008.
5 민영수, 김흥연, 김영균, "클라우스 컴퓨팅을 위한 분산 파일 시스템 기술," 한국정보과학회 학회지, 제5호, 2009.   과학기술학회마을
6 R. Chaiken, B. Jenkins, P.-A. Larson, B. Ramsey, D. Shakib, S. Weaver, and J. Zhou. "Scope: Easy and efficient parallel processing of massive data sets," VLDB'08, 2008.
7 Amazon Inc. Amazon Elastic Compute Cloud (Amazon EC2). http://aws.amazon.com/ec2.
8 Dhruba Borthakur, "The Hadoop Distributed File System: Architecture and Design," The Apache Software Foundation, 2007.
9 Jeffrey Dean and Sanjay Ghemawat, "MapReduce: Simplified Data Processing on Large Clusters," Sixth Symp. on Operating System Design and Implementation, San Francisco, USA, Dec. 2004.