CLOUD COMPUTING AND THE DNA DATA RACE

SEEE DIGIBOOK ON ENGINEERING & TECHNOLOGY, VOL. 1(2), JUNE 2020 PP. (92-98)
Abstract– The popularity of cloud computing has increased over the past few years due to the variety of problems it can solve, including the storing and processing of vast volumes of data. The type of data could range from something as simple as text to something as complex as DNA sequences. Big data analytics is a new trend resulting from the analysis of exceptionally huge amounts of data. It is vital to have a thorough understanding of the nature of such data in order to effectively classify massive amounts of information. This study’s objective is to examine data classification techniques and provide insight into their implementation in a distributed cloud environment..
Index Terms – Big data, data classification, Machine learning, Data Analytics
REFERENCE

1. Napoli, C., Pappalardo, G., Tramontana, E., & Zappalà, G. (2016). A cloud-distributed GPU architecture for pattern identification in segmented detectors big-data surveys. The Computer Journal, 59(3), 338-352.
2. Dai, H. (2018, March). Research on SVM improved algorithm for large data classification. In 2018 IEEE 3rd International Conference on Big Data Analysis (ICBDA) (pp. 181-185). IEEE.
3. Souza, A. M., & Amazonas, J. R. (2015). An outlier detect algorithm using big data processing and internet of things architecture. Procedia Computer Science, 52, 1010-1015.
4. Bello-Orgaz, G., Jung, J. J., & Camacho, D. (2016). Social big data: Recent achievements and new challenges. Information Fusion, 28, 45-59.
5. Tchito Tchapga, C., Mih, T. A., Tchagna Kouanou, A., Fozin Fonzin, T., Kuetche Fogang, P., Mezatio, B. A., & Tchiotsop, D. (2021). Biomedical image classification in a big data architecture using machine learning algorithms. Journal of Healthcare Engineering, 2021.
6. Peng, L., Peng, M., Liao, B., Huang, G., Li, W., & Xie, D. (2018). The advances and challenges of deep learning application in biological big data processing. Current Bioinformatics, 13(4), 352-359.
7. Fernández, A., del Río, S., Chawla, N. V., & Herrera, F. (2017). An insight into imbalanced big data classification: outcomes and challenges. Complex & Intelligent Systems, 3(2), 105-120.
8. Zhang, Y., Huang, T., & Bompard, E. F. (2018). Big data analytics in smart grids: a review. Energy informatics, 1(1), 1-24.
9. Ducange, P., Fazzolari, M., & Marcelloni, F. (2020). An overview of recent distributed algorithms for learning fuzzy models in Big Data classification. Journal of Big Data, 7(1), 1-29.


Arunkumar R 1 Udayakumar T 2
1 Department of Information Technology
2 Department of Computer Science and Engineering
Rathinam Technical Campus,
Coimbatore, Tamilnadu, India

Leave a Comment

Your email address will not be published. Required fields are marked *

Scroll to Top