Energy efficient resource utilization and load balancing in virtual machines using prediction algorithms

Udayasankaran, Mr P.; Thangaraj, S. John Justin

doi:10.1016/j.ijcce.2023.02.005

Search citation statements

Order By: Relevance

Paper Sections

Select...

B Challenges1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2023

2024

Publication Types

Select...

Article5

Preprint1

Relationship

Self Cite0

Independent6

Authors

Journals

Cited by 15 publications

(1 citation statement)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…One of the primary challenges arises from the dynamic nature of cloud workloads. Resource demands from cloud users fluctuate significantly over various timeframes, ranging from hourly to yearly, based on workload types and execution deadlines [63]- [65]. Despite this variability, cloud service providers are obligated to maintain high availability and deliver high-performance computing consistently.…”

Section: B Challengesmentioning

confidence: 99%

A Comprehensive Survey on Sustainable Resource Management in Cloud Computing Environments

Saxena,

Singh

2024

Preprint

View full text Add to dashboard Cite

show abstract

Section: B Challengesmentioning

confidence: 99%

A Comprehensive Survey on Sustainable Resource Management in Cloud Computing Environments

Saxena,

Singh

2024

Preprint

View full text Add to dashboard Cite

show abstract

A feature extraction and time warping based neural expansion architecture for cloud resource usage forecasting

Singh,

Sengupta,

Mehta

et al. 2024

Cluster Comput

View full text Add to dashboard Cite

Optimizing Resource Consumption and Reducing Power Usage in Data Centers, A Novel Mathematical VM Replacement Model and Efficient Algorithm

Rabieyan,

Yahyapour,

Jahnke

2024

J Grid Computing

View full text Add to dashboard Cite

This study addresses the issue of power consumption in virtualized cloud data centers by proposing a virtual machine (VM) replacement model and a corresponding algorithm. The model incorporates multi-objective functions, aiming to optimize VM selection based on weights and minimize resource utilization disparities across hosts. Constraints are incorporated to ensure that CPU utilization remains close to the average CPU usage while mitigating overutilization in memory and network bandwidth usage. The proposed algorithm offers a fast and efficient solution with minimal VM replacements. The experimental simulation results demonstrate significant reductions in power consumption compared with a benchmark model. The proposed model and algorithm have been implemented and operated within a real-world cloud infrastructure, emphasizing their practicality.

show abstract

Energy efficient resource utilization and load balancing in virtual machines using prediction algorithms

Cited by 15 publications

References 35 publications

A Comprehensive Survey on Sustainable Resource Management in Cloud Computing Environments

A Comprehensive Survey on Sustainable Resource Management in Cloud Computing Environments

A feature extraction and time warping based neural expansion architecture for cloud resource usage forecasting

Optimizing Resource Consumption and Reducing Power Usage in Data Centers, A Novel Mathematical VM Replacement Model and Efficient Algorithm

Contact Info

Product

Resources

About