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Efficient Cloud Resource Scheduling with an Optimized Throttled Load Balancing Approach

V. Dhilip Kumar1, J. Praveenchandar2, Muhammad Arif3,*, Adrian Brezulianu4, Oana Geman5, Atif Ikram3,6

1 Department of Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, 600062, India
2 Department of Computer Science and Engineering, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, 641114, India
3 Department of Computer Science, Superior University, Lahore, Pakistan
4 Faculty of Electronics Telecommunications and Information Technology, Gheorghe Asachi Technical University of Iasi, Iaşi, 700050, Romania
5 Department of Health and Human Development, Stefan cel Mare University of Suceava, Suceava, 720229, Romania
6 Faculty of Ocean Engineering Technology and Informatics, University Malaysia Terengganu, Kuala Nerus, Malaysia

* Corresponding Author: Muhammad Arif. Email: email

Computers, Materials & Continua 2023, 77(2), 2179-2188. https://doi.org/10.32604/cmc.2023.034764

Abstract

Cloud Technology is a new platform that offers on-demand computing Peripheral such as storage, processing power, and other computer system resources. It is also referred to as a system that will let the consumers utilize computational resources like databases, servers, storage, and intelligence over the Internet. In a cloud network, load balancing is the process of dividing network traffic among a cluster of available servers to increase efficiency. It is also known as a server pool or server farm. When a single node is overwhelmed, balancing the workload is needed to manage unpredictable workflows. The load balancer sends the load to another free node in this case. We focus on the Balancing of workflows with the proposed approach, and we present a novel method to balance the load that manages the dynamic scheduling process. One of the preexisting load balancing techniques is considered, however it is somewhat modified to fit the scenario at hand. Depending on the experimentation’s findings, it is concluded that this suggested approach improves load balancing consistency, response time, and throughput by 6%.

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Cite This Article

V. D. Kumar, J. Praveenchandar, M. Arif, A. Brezulianu, O. Geman et al., "Efficient cloud resource scheduling with an optimized throttled load balancing approach," Computers, Materials & Continua, vol. 77, no.2, pp. 2179–2188, 2023.



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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