An improved multi-objective eagle algorithm for virtual machine placement in cloud environment

Gabhane, Jyotsna P.; Pathak, Sunil; Thakare, Nita

doi:10.1007/s00542-023-05422-z

Cited by 3 publications

(1 citation statement)

References 27 publications

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“…In a recent work, Gabhane et al (2023) [16] introduced an enhanced variant of the multi-objective Eagle algorithm, targeting the optimization of resource utilisation, energy consumption, and migration cost. To augment the algorithm's performance, the authors incorporate several improvements, including an adaptive mutation operator and a modi ed mechanism for eagle updates.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimising Resource Consumption and Reducing Power Usage in datacentres: A Mathematical VM Replacement Model and Efficient Algorithm

Rabieyan

Yahyapour

2023

Preprint

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This study addresses the issue of power consumption in virtualized cloud datacentres by proposing a VM replacement model and an efficient algorithm. The model incorporates multi-objective functions, aiming to optimise VM selection based on weight and minimise resource utilisation disparities across hosts. Constraints are included to maintain balanced CPU, memory, and network bandwidth usage. The proposed algorithm offers a fast solution with minimal VM replacements. Experimental results in a simulation environment demonstrate significant reductions in power consumption compared to alternative models. The proposed model and algorithm are successfully implemented and operated within a real-world cloud infrastructure, emphasising their practicality.

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Section: Literature Reviewmentioning

confidence: 99%

Optimising Resource Consumption and Reducing Power Usage in datacentres: A Mathematical VM Replacement Model and Efficient Algorithm

Rabieyan

Yahyapour

2023

Preprint

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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

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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.

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VMP-ER: An Efficient Virtual Machine Placement Algorithm for Energy and Resources Optimization in Cloud Data Center

Rjeib,

Kecskemeti

2024

Algorithms

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Cloud service providers deliver computing services on demand using the Infrastructure as a Service (IaaS) model. In a cloud data center, several virtual machines (VMs) can be hosted on a single physical machine (PM) with the help of virtualization. The virtual machine placement (VMP) involves assigning VMs across various physical machines, which is a crucial process impacting energy draw and resource usage in the cloud data center. Nonetheless, finding an effective settlement is challenging owing to factors like hardware heterogeneity and the scalability of cloud data centers. This paper proposes an efficient algorithm named VMP-ER aimed at optimizing power consumption and reducing resource wastage. Our algorithm achieves this by decreasing the number of running physical machines, and it gives priority to energy-efficient servers. Additionally, it improves resource utilization across physical machines, thus minimizing wastage and ensuring balanced resource allocation.

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An improved multi-objective eagle algorithm for virtual machine placement in cloud environment

Cited by 3 publications

References 27 publications

Optimising Resource Consumption and Reducing Power Usage in datacentres: A Mathematical VM Replacement Model and Efficient Algorithm

Optimising Resource Consumption and Reducing Power Usage in datacentres: A Mathematical VM Replacement Model and Efficient Algorithm

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

VMP-ER: An Efficient Virtual Machine Placement Algorithm for Energy and Resources Optimization in Cloud Data Center

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