Efficient complexity based adaptive system for cloud resources

Kumar, Sarvesh; Sudha, Dyagala Naga; Anupama; Kannadasan, B.; Yadav, Ajay Singh; Goyal, Dinesh

doi:10.47974/JIM-1669

Open Access Research Article

Efficient complexity based adaptive system for cloud resources

^*Sarvesh KumarCorresponding authorkr.sarvi91@gmail.comDepartment of Computer Science and EngineeringBabu Banarasi Das UniversityLucknow, Uttar Pradesh, 226028, IndiaView full profile → , Dyagala Naga Sudhasudha51990@gmail.comDepartment of Management StudiesB. V. Raju Institute of TechnologyNarsapur, Telangana, IndiaView full profile → , Anupamaanupamadce@gmail.comDepartment of Computer Science and EngineeringDarbhanga College of EngineeringDarbhanga, Bihar, IndiaView full profile → , B. Kannadasankdasan9@gmail.comDepartment of Computer Science and Engineering120 Seethakathi Estate, Grand Southern Trunk RdB.S. Abdur Rahman Crescent Institute of Science and Technology, VandalurVandalur, Tamil Nadu, 600048, IndiaView full profile → , Ajay Singh Yadavajay29011984@gmail.comDepartment of MathematicsDelhi-NCR Campus, ModinagarSRM Institute of Science and TechnologyGhaziabad, Uttar Pradesh, IndiaView full profile → , Dinesh Goyaldinesh8dg@gmail.comPoornima Institute of Engineering and TechnologyJaipur, Rajasthan, IndiaView full profile →

* Corresponding author · click or hover a name for details

pp. 383–392Vol. 26Issue 3April 2023DOI: 10.47974/JIM-1669XML

Published Online:: 01 Apr 2023
Article type:: Research Article
Language:: EN
Article no.:: JIM-1669
Pages:: 383–392

Abstract

Cloud computing is a new IT concept, that is no longer solely applicable to the economic system however as nicely very beneficial in science. The issue of asset distribution and income expansion is likewise similarly significant, particularly about cloud security. This achieves the need of various displaying strategies including however not restricted, to security danger, asset assignment, and income boost models. These offerings are billed on a utilization basis. The cloud services are provided by the CSPs to the end users in an optimized way by using our mathematical proposed algorithm. This proposed algorithm is simulated in the cloud simulator. It prompts financially savvy arrangements by lessening the execution season of enormous application testing. As a piece of framework assets, cloud testing can accomplish its productivity by dealing with the boundaries like organization traffic, Circle Stockpiling, and Smash speed. In this paper, we propose another fluffy numerical model to accomplish a superior degree for the above boundaries. The results of the outcomes informs that the proposed algorithm CROS (Cloud Resource Optimized System) performances are better.

Keywords

Cloud resources Mathematical methodology Cloud services Cloud service providers End users Cloud simulation

Subject Classifications

Primary 93A30Secondary 49K15

References

[1] A. Ya. Matov,“ Optimization of the provision of computing resources with adaptive cloud infrastructure”, Data recording, storage and processing, Vol. 20, no.3, pp. 83-90, (in Ukrainian), (2018).
[2] Mell, P., and Grance, T. The NIST definition of cloud computing (2011).
[3] Tiwari, A., & Garg, R. Adaptive Ontology-Based IoT Resource Provisioning in Computing Systems. International Journal on Semantic Web and Information Systems (IJSWIS), 18(1), 1-18 (2022).
[4] Tiwari, A., & Garg, R. Orrs Orchestration of a Resource Reservation System Using Fuzzy Theory in High-Performance Computing: Lifeline of the Computing World. International Journal of Software Innovation (IJSI), 10(1), 1-28 (2022).
[5] Netto, M. A., Bubendorfer, K., and Buyya, R. SLA-based advance reservations with flexible and adaptive time QoS parameters. In International Conference on Service-Oriented Computing, pp. 119-131, (2007). Springer, Berlin, Heidelberg.
[6] Disha H. Parekh, R. Sridaran : An Analysis of Security Challenges in Cloud Computing. (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 4, No.1 (2013)
[7] Chouhan, A., Tiwari, A., Diwaker, C., & Sharma, A. Efficient Opportunities and Boundaries towards Internet of Things (IoT) Cost Adaptive Model. In 2022 IEEE Delhi Section Conference (DELCON), pp. 1-5 (2022, February). IEEE.
[8] Kumar, S., Dubey, K. K., Gautam, A. K., Verma, S., Kumar, V., & Mamodiya, U. Detection of recurring vulnerabilities in computing services. Journal of Discrete Mathematical Sciences and Cryptography, 25(4), 1063-1071 (2022).
[9] Tiwari, A., & Garg, R. ACCOS: A Hybrid Anomaly-Aware Cloud Computing Formulation-Based Ontology Services in Clouds. In ISIC, pp. 341-346 (2021).
[10] Rajkumar Buyya,” CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms”, Published in 2010.
[11] Rangaiah, Y. V., Sharma, A. K., Bhargavi, T., Chopra, M., Mahapatra, C., & Tiwari, A. A Taxonomy towards Blockchain based Multimedia content Security. In 2022 2nd International Conference on Innovative Sustainable Computational Technologies (CISCT), pp. 1-4 (2022, December). IEEE.
[12] Rohinidevi, V. V., Srivastava, P. K., Dubey, N., Tiwari, S., & Tiwari, A. A Taxonomy towards fog computing Resource Allocation. In 2022 2nd International Conference on Innovative Sustainable Computational Technologies (CISCT), pp. 1-5 (2022, December). IEEE.
[13] Singh, N. K., Jain, A., Arya, S., Gonzales, W. E. G., Flores, J. E. A., & Tiwari, A. Attack Detection Taxonomy System in cloud services. In 2022 2nd International Conference on Innovative Sustainable Computational Technologies (CISCT), pp. 1-5 (2022, December). IEEE.
[14] Tiwari, A., & Sharma, R. M. A Skywatch on the Challenging Gradual Progression of Scheduling in Cloud Computing. In Applications of Computing, Automation and Wireless Systems in Electrical Engineering, pp. 531-541, (2019). Springer, Singapore.
[15] Kumar, S., Srivastava, P. K., Pal, A. K., Mishra, V. P., Singhal, P., Srivastava, G. K., & Mamodiya, U. Protecting location privacy in cloud services. Journal of Discrete Mathematical Sciences and Cryptography, 25(4), 1053-1062 (2022).
[16] Tiwari, Ashish, and Ritu Garg. “Eagle Techniques In Cloud Computational Formulation.” International Journal of Innovative Technology and Exploring Engineering 8, no. 1 : 422-429 (2019).
[17] Kamble, S., Saini, D. K. J., Kumar, V., Gautam, A. K., Verma, S., Tiwari, A., & Goyal, D. Detection and tracking of moving cloud services from video using saliency map model. Journal of Discrete Mathematical Sciences and Cryptography, 25(4), 1083-1092 (2022).
[18] Tiwari, Ashish, and Ritu Garg. “Eagle Techniques In Cloud Computational Formulation.” International Journal of Innovative Technology and Exploring Engineering 8, no. 1 : 422-429 (2019).
[19] Laarichi, Y., & Barmaki, M. Explicit formulas for computing matrix trigonometric functions. Journal of Interdisciplinary Mathematics, 25(8), 2321-2331 (2022).
[20] Tong, J. F. User clustering based on Canopy+ K-means algorithm in cloud computing. Journal of Interdisciplinary Mathematics, 20(6-7), 1489-1492 (2017).
[21] Pragathi, B., Nayak, D. K., & Poonia, R. C. Mitigation of power quality issues for grid connected photo voltaic system using soft computing techniques. Journal of Interdisciplinary Mathematics, 23(2), 631-637 (2020).

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