A science cloud resource provisioning model using statistical analysis of job history

Proceedings - IEEE 9th International Conference on Dependable, Autonomic and Secure Computing, DASC 2011

Volumn , Issue , 2011, Pages 792-793

  Kim, Seoyoung ^a   Koh, Jung In ^a   Kim, Yoonhee ^a   Kim, Chongam ^b  

^a Sookmyung Women's University   (South Korea)

^b Seoul National University   (South Korea)

Author keywords

Job history; Principal component Analysis; Resource provisioning; Science Cloud

Indexed keywords

APPLICATION EXECUTION; EFFECTIVE FACTORS; EXECUTION ENVIRONMENTS; EXECUTION HISTORY; EXECUTION TIME; GUARANTEED PERFORMANCE; JOB EXECUTION; NODE-BASED; PCA (PRINCIPAL COMPONENT ANALYSIS); PRINCIPAL COMPONENTS; RESEARCH ENVIRONMENT; RESOURCE PROVISIONING; SCHEDULING MECHANISM; SERVICE PROVIDER; STATISTICAL TECHNIQUES; VIRTUAL MACHINES;

CLOUD COMPUTING; EMBEDDED SOFTWARE; SUPERCOMPUTERS;

PRINCIPAL COMPONENT ANALYSIS;

EID: 84862971252     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/DASC.2011.134     Document Type: Conference Paper

References (4)

1. Jolliffe, I.T. "Principal Component Analysis" Springer Verlag. 2002,
2. F.Berman et al., "Adaptive computing on the grid using apples," IEEE Transactions on Parallel and Distributed Systems, vol. 14, no. 4, pp.369-382, 2003.
3. H. Li, D. Groep, L. Wolters, "Efficient response time predictions by exploiting application and resource state similarities," in Proceedings of the 6th IEEE/ACM International Workshop on Grid Computing. IEEE Computer Society, 2005, pp. 234-241.
4. PRAGMA Grid and Cloud Monitoring home page, http://pragmagoc. rocksclusters.org