A PPR-based energy-efficient VM consolidation in cloud computing
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2024.15.3.17Keywords:
Cloud environment, Energy consumption, Energy-efficient approach, VM consolidation, VM migrationDimensions Badge
Issue
Section
License
Copyright (c) 2024 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The tendency to do more jobs while consuming less energy is crucial to energy efficiency in the cloud environment. To use less energy while performing more tasks at the best throughput, this study provides an energy-efficient technique (PPR_DWMMT_1.1) for VM consolidation in a cloud domain. Our approach uses the PPR to determine the upper threshold for overload detection and the lower threshold for underload detection. Additionally, PPR_DWMMT_1.1 considers the overall workload utilisation of the data centre when selecting a lower threshold, which could reduce VM migrations. Our proposed method, PPR DWMMT 1.1, is compared to the simulation results of the four reference techniques, IQR_MMT_1.5, LR_MC_1.2, MAD_MU_2.5, and THR_RS_0.8. Our solution has been demonstrated to use less energy, trigger fewer host shutdowns and live migrations, and achieve the best performance when compared to the other four approaches.Abstract
How to Cite
Downloads
Similar Articles
- Rama Rao J.V.G, Raja Gopal A.N.V.J, Ponnaganti S. Prasad, Illa V. Ram, Muthuvel B, Power quality improvement in BLDC motor drive using PFC converter , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- T. Malathi, T. Dheepak, Enhanced regression method for weather forecasting , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Manisha Pallvi, Carlson’s Trophic State Index of Shatiya Wetland in Gopalganj District of Bihar , The Scientific Temper: Vol. 12 No. 1&2 (2021): The Scientific Temper
- Manikant Tripathi, Sukriti Pathak, Ranjan Singh, Pankaj Singh, Pradeep K. Singh, Nivedita Prasad, Sadanand Maurya, Awadhesh Kumar Shukla, Adsorptive remediation of hexavalent chromium using agro-waste rice husk: Optimization of process parameters and functional groups characterization using FTIR analysis , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- Vijai K. Visvanathan, Karthikeyan Palaniswamy, Thanarajan Kumaresan, Green ammonia: catalysis, combustion and utilization strategies , The Scientific Temper: Vol. 14 No. 01 (2023): The Scientific Temper
- A. Anand, A. Nisha Jebaseeli, A comparative analysis of virtual machines and containers using queuing models , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- M. Menaha, J. Lavanya, Crop yield prediction in diverse environmental conditions using ensemble learning , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Kanwar D Singh, Rashmi Ashtt, Barriers to last mile connectivity: The role of crime in metro station accessibility , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- M. Rajalakshmi, V. Sulochana, Enhancing deep learning model performance in air quality classification through probabilistic hyperparameter tuning with tree-structured Parzen estimators , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- Vikas Yadav, Parul Nangia, Bisphenol-A Induced Changes in Blood Indices of Channa punctatus and Alleviation with Vitamin C , The Scientific Temper: Vol. 12 No. 1&2 (2021): The Scientific Temper
<< < 6 7 8 9 10 11 12 13 14 15 > >>
You may also start an advanced similarity search for this article.