Multi-Cloud Performance and Workflow Management

Authors

  • J Jayashree School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamilnadu, India
  • J Vijayashree School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamilnadu, India
  • N Ch S N Iyengar Department of Information Technology, Sreenidhi Institute of Science & Technology, Hyderabad, India
  • Syed Muzamil Basha School of Computer Science and Engineering, REVA University, Bengaluru, India

Keywords:

Cloud, Quality of service, Interface, Optimization

Abstract

Cloud Computing could be a new delivery model for IT services supported net protocols. It usually involves provisioning of dynamically climbable and sometimes virtualized resources at the infrastructure, platform and software system levels. It addresses completely different fundamentals like virtualization, measurability, ability, quality of service and failover mechanism .Cloud atmosphere differs from ancient environments on the very fact that it  is massively climbable, is encapsulated as associate abstract entity that delivers completely different levels of services to customers outside the Cloud,  is driven by economies of scale,  is dynamically organized (via virtualization or different approaches) and  is delivered on demand. Among different models, cloud environments are public, non-public or hybrid. A public cloud (a.k.a. external cloud) could be a cloud that gives cloud resources and services to the general public. a personal cloud (a.k.a. internal cloud) is associate enterprise in hand or hired cloud. In general, a hybrid cloud could be a composition of 2 or additional clouds of various models. Nonetheless, we define a hybrid cloud as a composition of 1 public cloud and one non-public cloud. Such a cloud is associate atmosphere during which associate enterprise has its own non-public cloud that gives and manages some internal resources and solely uses external resources provided by the general public cloud once required.

References

Irvine, C., & Levin, T. (2000). Quality of security service: an introduction. NAVAL POSTGRADUATE SCHOOL MONTEREY CA.

Lindskog, S. (2005). Modeling and tuning security from a quality of service perspective (pp. 0668-0668). Chalmers University of Technology.

Dart, E., Rotman, L., Tierney, B., Hester, M., & Zurawski, J. (2013, November). The science dmz: A network design pattern for data-intensive science. In Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis (pp. 1-10).

Force, J. T., & Initiative, T. (2013). Security and privacy controls for federal information systems and organizations. NIST Special Publication, 800(53), 8-13.

Agrawal, D., El Abbadi, A., Emekci, F., & Metwally, A. (2009, March). Database management as a service: Challenges and opportunities. In 2009 IEEE 25th International Conference on Data Engineering (pp. 1709-1716). IEEE.

Alzain, M. A., & Pardede, E. (2011, January). Using multi shares for ensuring privacy in database-as-a-service. In 2011 44th Hawaii International Conference on System Sciences (pp. 1-9). IEEE.

Chase, J., & Thummala, V. (2014). A guided tour of SAFE GENI. Duke University Department of Computer Science Tech Report, CS-2014-002.

Sreedhar, S., Ahmed, S., Flora, P., Hemanth, L. S., Aishwarya, J., & Naik, R. (2021, January). An Improved Approach of Unstructured Text Document Classification Using Predetermined Text Model and Probability Technique. In Proceedings of the First International Conference on Advanced Scientific Innovation in Science, Engineering and Technology, ICASISET 2020, 16-17 May 2020, Chennai, India.

Al-Shammari, N. K., Alzamil, A. A., Albadarn, M., Ahmed, S. A., Syed, M. B., Alshammari, A. S., & Gabr, A. M. (2021). Cardiac Stroke Prediction Framework using Hybrid Optimization Algorithm under DNN. Engineering, Technology & Applied Science Research, 11(4), 7436-7441.

Yu, T., Zhang, Y., & Lin, K. J. (2007). Efficient algorithms for web services selection with end-to-end qos constraints. ACM Transactions on the Web (TWEB), 1(1), 6-es.

Hand, R., Ton, M., & Keller, E. (2013, November). Active security. In Proceedings of the Twelfth ACM Workshop on Hot Topics in Networks (pp. 1-7).

Ahmed, S. T., Sreedhar Kumar, S., Anusha, B., Bhumika, P., Gunashree, M., & Ishwarya, B. (2018, November). A Generalized Study on Data Mining and Clustering Algorithms. In International Conference On Computational Vision and Bio Inspired Computing (pp. 1121-1129). Springer, Cham.

Raja, D. K., Pushpa, S., & Kumar, B. N. (2016, February). Multidimensional distributed opinion extraction for sentiment analysis-a novel approach. In 2016 2nd International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB) (pp. 35-39). IEEE.

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Published

2022-12-26

How to Cite

J Jayashree, J Vijayashree, N Ch S N Iyengar, & Syed Muzamil Basha. (2022). Multi-Cloud Performance and Workflow Management. International Journal of Human Computations & Intelligence, 1(4), 18–28. Retrieved from https://milestoneresearch.in/JOURNALS/index.php/IJHCI/article/view/45

Issue

Vol. 1 No. 4 (2022): November/December - Issue - 04

Section

Articles

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Copyright (c) 2022 J Jayashree, J Vijayashree, N Ch S N Iyengar, Syed Muzamil Basha

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