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A Harris Hawk Optimisation system for energy and resource efficient virtual machine placement in cloud data centers.

Madhusudhan H S¹, Satish Kumar T², Punit Gupta³

¹Department of Computer Science & Engineering, Vidyavardhaka College of Engineering, Mysuru, Karnataka, India.

|August 11, 2023

Summary

This study introduces a Harris Hawk Optimization (HHO) model for efficient virtual machine placement in cloud data centers. The HHO model significantly reduces power consumption and improves resource utilization for optimized cloud infrastructure.

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Area of Science:

Computer Science
Cloud Computing
Optimization Algorithms

Background:

Cloud data centers face increasing energy demands due to service migration and expanding infrastructure.
Efficient resource allocation is crucial for optimizing power usage and operational costs in cloud environments.
Virtual machine placement strategies directly impact cloud resource utilization and energy consumption.

Purpose of the Study:

To present a novel virtual machine placement technique using the Harris Hawk Optimization (HHO) model.
To optimize virtual machine placement for reduced load and power consumption on cloud data center hosts.
To evaluate the effectiveness of the HHO model against existing methods in dynamic cloud environments.

Main Methods:

Developed a virtual machine placement technique based on the Harris Hawk Optimization (HHO) model.
Utilized PlanetLab's real-time workload traces for performance evaluation.
Compared the HHO model with Particle Swarm Optimization (PSO) and Best Fit Decreasing (BFD) algorithms.

Main Results:

The HHO algorithm improved execution time by 4% and resource utilization by 17%.
Achieved a 27% reduction in power consumption and a 16% decrease in Service Level Agreement (SLA) violations.
Demonstrated superior performance in handling underloaded and overloaded conditions through simulation scenarios.

Conclusions:

The proposed HHO model offers an efficient and effective solution for virtual machine placement in cloud data centers.
HHO is suitable for real-world cloud infrastructures due to its effectiveness in dynamic and uncertain environments.
Optimized virtual machine placement using HHO leads to significant energy savings and improved operational efficiency.