Reducing Energy Consumption in Green Cloud Computing

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Lestari Margatama

Abstract

Wide-ranging cloud data centres are required for the provision of numerous software solutions across a wide range of industry verticals. Power usage is expected to rise as cloud data centres ramp up operations and expand their footprints. Here, a single-objective optimization is accomplished through the application of a Simple Genetic Algorithm (SGA). The Artificial Neural Network (ANN) uses the genetic optimization strategy to estimate the existing resources based on their features and role characteristics, and Dynamic voltage frequency scaling (DVFS) has also been utilised to reduce energy usage. The multi-objective system is empowered to reduce energy consumption because of the overall recommended method. OpenStack simulation tools were used in this context to arrive at an accurate conclusion prior to implementing on the cloud. Open Stack provides a single computer node with the ability to model and simulate a data centre. Energy usage and virtual machine migration were used to evaluate the results of the project.

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How to Cite
Margatama, L. . (2021). Reducing Energy Consumption in Green Cloud Computing. Helix - The Scientific Explorer | Peer Reviewed Bimonthly International Journal, 11(2), 6-15. Retrieved from https://helixscientific.pub/index.php/home/article/view/357
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