:: International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies
http://TuEngr.com
ISSN 2228-9860
eISSN 1906-9642
CODEN: ITJEA8
FEATURE PEER-REVIEWED ARTICLE
Vol.11(16) (2020) |
Saleh M. Alqahtani, Hamza Arishi (College of Computing and Informatics, Saudi Electronic University, SAUDI ARABIA).
Disciplinary: Computer and Information Sciences, Digital Business Management and Service.
DOI: 10.14456/ITJEMAST.2020.315
Keywords: Cloud service; Proactive fault tolerance; Reactive fault tolerance; Cloud computing threat; Cloud computing risks; Cloud computing vulnerabilities, Cloud fault detection.
Paper ID: 11A16F
Cite this article:
Alqahtani, S.M., Arishi, H.(2020). A Review on the Tools and Techniques for Effective Failure Detection and Prediction in Cloud Computing. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies, 11(16), 11A16F, 1-10. http://doi.org/10.14456/ITJEMAST.2020.315
References:
Amin, Z., Singh, H., & Sethi, N. (2015). Review on fault tolerance techniques in cloud computing. International Journal of Computer Applications, 116(18).
Dwivedi, U., & Dev, H. (2018). A Review on Fault Tolerance Techniques and Algorithms in Green Cloud Computing. Journal of Computational and Theoretical Nanoscience, 15(9-10), 2689-2700.
Gao, W., Alqahtani, A. S., Mubarakali, A., & Mavaluru, D. (2019). Developing an innovative soft computing scheme for prediction of air overpressure resulting from mine blasting using GMDH optimized by GA. Engineering with Computers, 1-8.
Gill, S. S., & Buyya, R. (2018). Failure management for reliable cloud computing: A taxonomy, model, and future directions. Computing in Science & Engineering.
Moges, F. F., & Abebe, S. L. (2019). Energy-aware VM placement algorithms for the OpenStack Neat consolidation framework. Journal of Cloud Computing, 8(1), 2.
Pannu, H. S., Liu, J., Guan, Q., & Fu, S. (2012). AFD: Adaptive failure detection system for cloud computing infrastructures. In 2012 IEEE 31st International Performance Computing and Communications Conference (IPCCC) (pp. 71-80).
Rajasekar, S., Philominathan, P., & Chinnathambi, V. (2006). Research methodology. arXiv preprint physics/0601009.
Shihab, L. A. (2020). Technological Tools for Data Security in the Treatment of Data Reliability in Big Data Environments. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies, 11(9), 11A9M, 1-13.
Suryateja, P. S. (2018). Threats and vulnerabilities of cloud computing: A review. International Journal of Computer Sciences and Engineering, 6(3), 297-302.
Talia, D. (2019). A view of programming scalable data analysis: from clouds to exascale. Journal of Cloud Computing, 8(1), 4.
Tchernykh, A., Schwiegelsohn, U., Talbi, E. G., & Babenko, M. (2019). Towards understanding uncertainty in cloud computing with risks of confidentiality, integrity, and availability. Journal of Computational Science, 36, 100581.
Other issues:
Vol.11(16)(2020)
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