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
- V. Babydeepa, K. Sindhu, Piecewise adaptive weighted smoothing-based multivariate rosenthal correlative target projection for lung and uterus cancer prediction with big data , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- S. K. Mishra, BIOREMEDIATION: A BIOTECHNOLOGICAL APPROACH TOWARD ENVIRONMENTAL MANAGEMENT , The Scientific Temper: Vol. 1 No. 01 (2010): The Scientific Temper
- Neerav Nishant, Nisha Rathore, Vinay Kumar Nassa, Vijay Kumar Dwivedi, Thulasimani T, Surrya Prakash Dillibabu, Integrating machine learning and mathematical programming for efficient optimization of electric discharge machining technique , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Modenisha U, Ritha. W, Fueling Sustainability: A Cost-Benefit Analysis of RDF and Sewage Sludge as Alternative Fuels in Cement Production , The Scientific Temper: Vol. 16 No. 09 (2025): The Scientific Temper
- P. Hepsibah Kenneth, E. George Dharma Prakash Raj, Priority based parallel processing multi user multi task scheduling algorithm , The Scientific Temper: Vol. 16 No. 02 (2025): The Scientific Temper
- Josephine Theresa S, Graph Neural Network Ensemble with Particle Swarm Optimization for Privacy-Preserving Thermal Comfort Prediction , The Scientific Temper: Vol. 16 No. 12 (2025): The Scientific Temper
- Sharada C, T N Ravi, S Panneer Arokiara, Lancaster sliced regressive keyword extraction based semantic analytics on social media documents , The Scientific Temper: Vol. 16 No. 08 (2025): The Scientific Temper
- T. Ramyaveni, V. Maniraj, Hyperparameter tuning of diabetes prediction using machine learning algorithm with pelican optimization algorithm , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Seema Yadav, Problems and Perspectives in Sustainable Environment in the World: A Legal Study , The Scientific Temper: Vol. 12 No. 1&2 (2021): The Scientific Temper
- C. Agilan, Lakshna Arun, Optimization-based clustering feature extraction approach for human emotion recognition , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
<< < 7 8 9 10 11 12 13 14 15 16 > >>
You may also start an advanced similarity search for this article.

