Megha Guptaa,*, Laxmi Ahujaa, and Ashish Sethb
| 1. Kannadhasan, S., Nagarajan, R. and Thenappan, S. Intrusion Detection Techniques Based Secured Data Sharing System for Cloud Computing Using MSVM. In2022 9th International Conference on Computing for Sustainable Global Development (INDIACom), IEEE, pp. 50-56, 2022
2. Ujjwal K.C., Garg S., Hilton J., Aryal J. and Forbes-Smith, N. Cloud Computing in natural hazard modeling systems: Current research trends and future directions. International Journal of Disaster Risk Reduction, vol. 38, pp. 101188, 2019.
3. Cai F., Zhu N., He J., Mu P., Li W., andYu Y.Survey of access control models and technologies for cloud computing. Cluster Computing, vol. 22, pp. 6111-6122, 2019
4. Atieh A.T.The next generation cloud technologies: a review on distributed cloud, fog and edge computing and their opportunities and challenges. ResearchBerg Review of Science and Technology, vol. 1, no. 1, pp.1-15, 2021
5. Katal, A., Dahiya, S. and Choudhury, T.Energy efficiency in cloud computing data centers: a surveyon software technologies. Cluster Computing, pp.I-31, 2022
6. Sunyaev, A. and Sunyaev, A.Cloud computing. J111ernetComputing: Principles of Distributed Systems and Emerging/111ernet-Based Technologies, pp. 195-236, 2020.
7. Aujla, G.S. and Kumar,N.MEnSuS: An efficient scheme for energy management with sustainability]jty of cloud data centers in edge-cloud environment. Future Generation Computer Systems, vol. 86, pp. 1279-1300, 2018
8. Mansouri, N., Javidi, MM.andMohammad Hasani Zade, B.Using data mining techniques to improve replica management in cloud environment. Soft Computing, vol. 24, pp. 7335-7360, 2020
9. lndu, I., Anand, P.R. and Bhaskar, V. Identity and access management in cloud environment: Mechanisms and challenges. Engineering science and technology, an international journal, vol. 21, no. 4, pp.574-588, 2018.
10. Chaudhary R., Aujla G.S., Kumar N. and Rodrigues JJ.Optimized big data management across multi-clouddatacenters: Software-defined-network-based analysis. IEEE Communications Magazine, vol. 56, no. 2, pp.118-126, 2018
11. lI. Diene B., Rodrigues JJ., Diallo O., Ndoye, EJIM. And Korotaev, V.V. Data management techniques for Internet of Things. Mechanical Systems and Signal Processing,2020, vol. 138, pp.106564.
12. Zhu Y., Tan Y., Luo X., andHe Z.Big data management for cloud-enabled geological information services. Scientific Programming, pp.1-13, 2018
13. Agarwal, M. and Srivastava G.M.S. "Big'' data management in cloud computing environment. In Harmony Search and Nature Inspired Optimization Algorithms: Theory andApplica1ions, ICHSA2018, Springer Singapore, pp.707-716, 2019.
14. Ding D., Fan X., Zhao Y., Kang K., Yin Q. and Zeng J.Q-learning based a dynamic task scheduling for energy-efficient cloud computing. Future Generation Computer Systems, vol. 108, pp.361-371, 2020.
15. Shamshir band, S., Fathi, M., Chrono Poulos, A.T., Montieri, A., Palumbo, F. and Pescape, A. Computational intelligence intrusion detection techniques in mobile cloud computing environments: Review, taxonomy, and open research issues. Journal of Information Security and Applications, vol. 55, pp. 102582, 2020
16. Razaque A., Shaldanbayeva N., AJotaibi B., Alotaibi M., Murat A. and Alotaibi A.Big data handling approach for unauthorized cloud computing access. Electronics, vol. 11, no. 1, pp. 137, 2022
17. Kimmel J.C., Mcdole AD.,Abdelsalam M., Gupta M. and Sandhu R.Recurrent neural networks based online behavioural malware detection techniques for cloud infrastructure. IEEE Access, vol. 9, pp. 68066-68080, 2021
18. Namasudra S.An improved attribute-based encryption technique towards the data security cloud computing. Concurrency and Computation: Practice and Experience, vol. 31, no. 3, pp. e4364, 2019
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|||Yunjie Lei, Ying Ma, Shunyi Chen, Yu Sun, and Keshou Wu. Fuzzy Multi-Attribute Decision Making for Software Defect Detection Model Evaluation [J]. Int J Performability Eng, 2020, 16(1): 78-86.|
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|||Yuping Li. Optimization of Multi-Objective Virtual Machine based on Ant Colony Intelligent Algorithm [J]. Int J Performability Eng, 2019, 15(9): 2494-2503.|
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