Improved performance optimization for massive small files in cloud computing environment-Reference-Cited by-同舟云学术

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Improved performance optimization for massive small files in cloud computing environment

Published:2016-11-17 Issue:2 Volume:265 Page:305-317
ISSN:0254-5330
Container-title:Annals of Operations Research
language:en
Short-container-title:Ann Oper Res

Author:

Choi Chang,Choi Chulwoong,Choi Junho,Kim Pankoo

Funder

Ministry of Education

Ministry of Science, ICT and Future Planning

Publisher

Springer Science and Business Media LLC

Subject

Management Science and Operations Research,General Decision Sciences

Link

http://link.springer.com/article/10.1007/s10479-016-2376-0/fulltext.html

Reference11 articles.

1. Bhandarkar, M. (2010). MapReduce programming with apache Hadoop. Parallel & Distributed Processing (IPDPS), 2010 IEEE International Symposium on. IEEE, 2010.

2. Choi, C., Choi, J., & Kim, P. (2014). Ontology based access control model for security policy reasoning in cloud computing. Journal of Supercomputing, 67(3), 711–722.

3. Choi, J., Choi, C., Ko, B., & Kim, P. (2014). A method of DDoS attack detection using HTTP packet pattern and rule engine in cloud computing environment. Journal of Soft Computing, 18(9), 1697–1703.

4. Choi, J., Choi, C., Yim, K., Kim, J., & Kim, P. (2013). Intelligent recongurable method of cloud computing resources for multimedia data delivery. Journal of Informatica, 24(3), 381–394.

5. Dean, J., & Ghemawat, S. (2008). MapReduce: Simplified data processing on large clusters. Communications of the ACM, 51(1), 107–113.

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3. Small files’ problem in Hadoop: A systematic literature review;Journal of King Saud University - Computer and Information Sciences;2021-09

4. Enhancing HDFS with a full-text search system for massive small files;The Journal of Supercomputing;2021-01-04

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