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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- Korean Institute of Information Scientists and Engineers Journal of Computing Science and Engineering Journal of Computing Science and Engineering Vol.10 No.1
- 발행연도
- 2016.3
- 수록면
- 21 - 31 (11page)
이용수
초록· 키워드
오류제보하기
With the application and development of biomedical techniques such as next-generation sequencing, mass spectrometry, and medical imaging, the amount of biomedical data have been growing explosively. In terms of processing such data, we face the problems surrounding big data, highly intensive computation, and high dimensionality data. Fortunately, cloud computing represents significant advantages of resource allocation, data storage, computation, and sharing and offers a solution to solve big data problems of biomedical research. In order to improve the efficiency of resource management in cloud computing, this paper proposes a clustering method and adopts Radial Basis Function in order to compress comprehensive data sets found in biology and medicine in high quality, and stores these data with resource management in cloud computing. Experiments have validated that with such a data-compression-based resource management in cloud computing, one can store large data sets from biology and medicine in fewer capacities. Furthermore, with reverse operation of the Radial Basis Function, these compressed data can be reconstructed with high accuracy.
목차
Abstract
Ⅰ. INTRODUCTION
Ⅱ. RELATED WORK
Ⅲ. DATA-COMPRESSION-BASED RESOURCE MANAGEMENT IN CLOUD COMPUTING
Ⅳ. EXPERIMENTS
Ⅴ. CONCLUSION AND FUTURE WORK
REFERENCES
참고문헌 (22)
참고문헌 신청
J. Qin, Y. Li, Z. Cai, S. Li, J. Zhu, F. Zhang, Y. Peng, S. Liang, W. Zhang, Y. Guan, et al., “A metagenome-wide association study of gut microbiota in type 2 diabetes,” Nature, vol. 490, no. 7418, pp. 55-60, 2012.
M. C. Schatz, B. Langmead, and S. L. Salzberg, “Cloud computing and the DNA data race,” Nature Biotechnology, vol. 28, no. 7, pp. 691-693, 2010.
“Gathering clouds and a sequencing storm: why cloud computing could broaden community access to next-generation sequencing,” Nature Biotechnology, vol. 28, no. 1, 2010. http://dx.doi.org/10.1038/nbt0110-1.
A. Rosenthal, P. Mork, M. H. Li, J. Stanford, D. Koester, and P. Reynolds, “Cloud computing: a new business paradigm for biomedical information sharing,” Journal of Biomedical Informatics, vol. 43, no. 2, pp. 342-353, 2010.
E. Pennisi, “Human genome 10th anniversary. Will computers crash genomics?,” Science, vol. 11, no. 6018, pp. 666-668, 2011.
M. C. Schatz, B. Langmead, and S. L. Salzberg, “Cloud computing and the DNA data race,” Nature Biotechnology, vol. 28, no. 7, pp. 691-693, 2010.
“Gathering clouds and a sequencing storm: why cloud computing could broaden community access to next-generation sequencing,” Nature Biotechnology, vol. 28, no. 1, 2010. http://dx.doi.org/10.1038/nbt0110-1.
A. Rosenthal, P. Mork, M. H. Li, J. Stanford, D. Koester, and P. Reynolds, “Cloud computing: a new business paradigm for biomedical information sharing,” Journal of Biomedical Informatics, vol. 43, no. 2, pp. 342-353, 2010.
E. Pennisi, “Human genome 10th anniversary. Will computers crash genomics?,” Science, vol. 11, no. 6018, pp. 666-668, 2011.
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UCI(KEPA) : I410-ECN-0101-2016-569-002774728