Efficient cost evaluation of real time applications using mathematical model in computing environment

Pachar, Sunita; Kapila, Dhiraj; Cotrina-Aliaga, Juan Carlos; Arias-Gonzáles, José Luis; Yadav, Sanjay; Aggarwal, Sandeep; Mamodiya, Udit

doi:10.47974/JIM-1679

Open Access Research Article

Efficient cost evaluation of real time applications using mathematical model in computing environment

^*Sunita PacharCorresponding authorsunita.pachar@gmail.comIBM DepartmentGLA UniversityMathura, Uttar Pradesh, IndiaView full profile → , Dhiraj Kapiladhiraj.23509@lpu.co.inLovely Professional UniversityPhagwara, Punjab, IndiaView full profile → , Juan Carlos Cotrina-Aliagajuan.cotrina@upsjb.edu.peUniversidad Privada San Juan BautistaChincha, Chincha, PerúView full profile → , José Luis Arias-Gonzálesa20225538@pucp.edu.pePontificia Universidad Católica del PerúPerúView full profile → , Sanjay YadavSanjayyadav@kluniversity.inKoneru Lakshmaaiah Education Foundation VaddeswaramGuntur, Andhra Pradesh, 522002, IndiaView full profile → , Sandeep Aggarwalsandeepaggarwal10@gmail.comDepartment of Computer Science and ApplicationsD.A.V. CollegeAbohar, Punjab, IndiaView full profile → , Udit Mamodiyaudit.mamodiya@poornima.orgAICTE-IDEA Lab CoordinatorPoornima Institute of Engineering and TechnologyJaipur, Rajasthan, IndiaView full profile →

* Corresponding author · click or hover a name for details

pp. 531–541Vol. 26Issue 3April 2023DOI: 10.47974/JIM-1679XML

Published Online:: 01 Apr 2023
Article type:: Research Article
Language:: EN
Article no.:: JIM-1679
Pages:: 531–541

Abstract

The cloud real time services are provided in an efficient manner now a days in rapid way. The Cloud computing objective is an on-request administration model for end clients. The on-request administration model comprises memory stockpiling, equipment on the board, data handling, and different IoT applications utilizing numerical programming rationales with the upgraded fluffy model. Money saving advantage analysis is the thing that everybody should do as such as to consider a strong or a proficient framework. In any case, while thinking out on cost and advantage examination, we additionally need to figure out factors that truly influence the advantages and expenses of the framework. In creating quotes for a framework, we really want to think about some of the cost components. A few components among them are equipment, staff, office, working, and supply costs. By utilizing the fluffy model, the end clients get the best ideal cloud administrations. The proposed system provides mathematical model of rough set theory. The proposed model provides an adequate cost to the end users in terms of cloud services. For giving cloud administrations in a streamlined manner the fluffy rationale is assuming a significant part. Our proposed calculation is performing better under pressure from different calculations. The proposed algorithm finds the proposed system most suitable w.r.t cost. The reproduction of our calculation is finished in simulation system of the cloud environment.

Keywords

Cloud parameters Resource issues Approximation logic Cloud parameters Approximation process Cloud simulation

Subject Classifications

Primary 93A30Secondary 49K15

References

[1] Mell, P., and Grance, T. The NIST definition of cloud computing (2011).
[2] Flexera, “Flexera 2020 State of the Cloud Report”, https:// info. flexera.com /SLO-CM-REPORT-State-of-the-Cloud-2020, [Online; accessed 25-Feb-2021] .
[3] Nick Galov, “The Latest Cloud Computing Trends – 31+ Telling Facts”, https://hostingtribunal.com/blog/cloud-computing-trends/, [Online; accessed 25-Feb-2021].
[4] 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)).
[5] Gartner, “Gartner Forecasts Worldwide Public Cloud End-User Spending to Grow 18% in 2021”, https://www.gartner.com/en/newsroom/press-releases/2020-11-17-gartner-forecasts-worldwide-public-cloud-end-user-spending-to-grow-18-percent-in-2021, [Online; accessed 25-Feb-2021].
[6] Tiwari, Ashish, Sarvesh Kumar, Neeraj Baishwar, Sunil Kumar Vishwakarma, and Prabhishek Singh. “Efficient Cloud Orchestration Services in Computing.” In Proceedings of 3rd International Conference on Machine Learning, Advances in Computing, Renewable Energy and Communication, pp. 739-746. Springer, Singapore (2022).
[7] Rajkumar Buyya,”CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms”, Published in 2010.
[8] 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).
[9] 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).
[10] Tiwari, A., & Sharma, R. M. OCC: A Hybrid Multiprocessing Computing Service Decision Making Using Ontology System. International Journal of Web-Based Learning and Teaching Technologies (IJWLTT), 16(4), 96-116 (2021).
[11] Liu, Y., Esseghir, M., and Boulahia, L. M. Evaluation of parameters importance in cloud service selection using rough sets. Applied Mathematics, 7(06), 527 (2016).
[12] Tiwari, A., Sah, M. K., & Malhotra, A. (2015, September). Effective service Utilization in Cloud Computing exploitation victimisation rough pure mathematics as revised ROSP. In 2015 4th International Conference on Reliability, Infocom Technologies and Optimization (ICRITO)(Trends and Future Directions) (pp. 1-6). IEEE.
[13] Tiwari, A., & Sharma, R. M. Realm Towards Service Optimization in Fog Computing. International Journal of Fog Computing (IJFC), 2(2), 13-43 (2019).
[14] 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). Springer, Berlin, Heidelberg (2007).
[15] Tiwari, A., & Garg, R. Reservation System for Cloud Computing Resources (RSCC): Immediate Reservation of the Computing Mechanism. International Journal of Cloud Applications and Computing (IJCAC), 12(1), 1-22 (2022).
[16] Pawlak, Z. Rough sets. International Journal of Computer and Information Sciences, 11(5), 341-356 (1982).
[17] Kumar Sharma, A., Tiwari, A., Bohra, B., & Khan, S. A Vision towards Optimization of Ontological Datacenters Computing World. International Journal of Information Systems & Management Science, 1(2) (2018).
[18] Tiwari, A., & Sharma, R. M. (2018). Rendering Form Ontology Methodology for IoT Services in Cloud Computing. International Journal of Advanced Studies of Scientific Research, 3(11).
[19] Rangaiah, Y. V., Sharma, A. K., Bhargavi, T., Chopra, M., Mahapatra, C., & Tiwari, A. (2022, December). A Taxonomy towards Blockchain based Multimedia content Security. In 2022 2nd International Conference on Innovative Sustainable Computational Technologies (CISCT) (pp. 1-4). IEEE.
[20] Rohinidevi, V. V., Srivastava, P. K., Dubey, N., Tiwari, S., & Tiwari, A. (2022, December). A Taxonomy towards fog computing Resource Allocation. In 2022 2nd International Conference on Innovative Sustainable Computational Technologies (CISCT) (pp. 1-5). IEEE.
[21] Amit Kumar Gupta, Pushpa Gothwal, Dinesh Goyal & Carlos M. Travieso-Gonzalez. IoT-Galvanized pandemic special E-Toilet for generation of sanitized environment, Journal of Discrete Mathematical Sciences and Cryptography, DOI: 10.1080/09720529.2022.2068607 (2022).
[22] Amit Kumar Gupta, Vijander Singh, Priya Mathur & Carlos M. Travieso-Gonzalez. Prediction of COVID-19 pandemic measuring criteria using support vector machine, prophet and linear regression models in Indian scenario, Journal of Interdisciplinary Mathematics (2020), DOI: https://doi.org/10.1080/09720502.2020.1833458.
[23] Jitendra Singh Yadav, Amit Kumar Gupta & Arjit Saxena. A review on gender identification using machine learning based on fingerprints, Journal of Information and Optimization Sciences, 40:5, 1121-1129 (2019), DOI: https://doi.org/10.1080/02522667.2019.1638002.

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