International Journal of Advanced Academic Studies International, Peer reviewed, Refereed, Open access, Multidisciplinary Journal

2022, Vol. 4, Issue 3, Part C


Optimizing load balancing for green cloud via efficient scheduling


Author(s): Manideep Yenugula

Abstract:
The primary objective of cloud service providers is to maximize profits via the optimal use of cloud computing resources. Cloud technology is a business-oriented concept that aims at offering online IT resources as well as IT services on demand through a pay-as-you-go approach. Optimization of cloud servers on a regular basis is one of the trickiest parts of cloud computing. In order to promote the idea of green computing and increase host machine efficiency, load balancing in cloud datacenters is the major focus. In order to restore equilibrium to the data center's workload, it is necessary to use migration methods to move the virtual machines from the overloaded hosts to the less demanding host. We provide a Bacterial Foraging Optimization Algorithms (BFOA) for optimizing cloud servers, which is based on thresholds, in this study. For cloud service cost reduction, BFOA decreases the number of host systems that need to be switched on, in contrast to conventional server optimization algorithms that just take CPU, RAM, and BW use into account when scheduling resources. Through efficient use of resources, our method may help the cloud sector reduce service costs.


DOI: 10.33545/27068919.2022.v4.i3c.1125

Pages: 224-230 | Views: 439 | Downloads: 132

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International Journal of Advanced Academic Studies
How to cite this article:
Manideep Yenugula. Optimizing load balancing for green cloud via efficient scheduling. Int J Adv Acad Stud 2022;4(3):224-230. DOI: 10.33545/27068919.2022.v4.i3c.1125
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