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
- Dhara B. Makwana, Adwait Mevada, Diversity and Green Synthesis of Various Metal Nanoparticles (MNPs) , The Scientific Temper: Vol. 16 No. 11 (2025): The Scientific Temper
- Veena Pande, Manish Pande, MOLECULAR DIVERSITY OF ECTOMYCORRHIZAL FUNGI OF CENTRAL HIMALAYA OF INDIA: AN IMPORTANT COMPONENT OF FOREST ECOSYSTEM , The Scientific Temper: Vol. 1 No. 01 (2010): The Scientific Temper
- Sivakumar S, Rajasekaran Kondareddy, Kalyani Ayyemperumal, Building SaaS solutions using microsoft azure for achieving safe and secure tax related software , The Scientific Temper: Vol. 14 No. 02 (2023): The Scientific Temper
- Navjot Singh, Sultan Singh, Demographic perception of customers towards dairy marketing practices: An empirical study , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Teklu Hailu, Regasa Begna , Pre-extension demonstration of inter-cropping of improved forages with food and cash crops at Semen Bench Woreda, Southwest Ethiopia , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- Archana Verma, Application of metaverse technologies and artificial intelligence in smart cities , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- Rajeev P. R., K. Aravinthan, A novel approach for metrics-based software defect prediction using genetic algorithm , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- S. Gomathi, C. Radhika, A secure messaging application using steganography and AES encryption a dual-layer secure messaging system , The Scientific Temper: Vol. 16 No. 02 (2025): The Scientific Temper
- Bommaiah Boya, Premara Devaraju, Integrating clinical and ECG data for heart disease prediction: A hybrid deep learning approach based on two modalities with particle swarm optimization , The Scientific Temper: Vol. 16 No. 05 (2025): The Scientific Temper
- Merla Agnes Mary, Britto Ramesh Kumar, Hybrid GAN with KNN - SMOTE Approach for Class-Imbalance in Non-Invasive Fetal ECG Monitoring , The Scientific Temper: Vol. 16 No. 09 (2025): The Scientific Temper
<< < 27 28 29 30 31 32 33 34 35 36 > >>
You may also start an advanced similarity search for this article.

