Effective Load Balancing on Servers Using Virtual Machines for ‎Cloud Computing Environment Using Green Computing and The Skewness Algorithm

Authors and Affiliations

  • T. Swathi Associate Professor, Department of Computer Science and Engineering, G. Pulla Reddy Engineering College, Kurnool, India
  • S. Saravanan Associate Professor, Department of Computer Science and Engineering, Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology, ‎Avadi, Chennai, Tamilnadu, India – 600062
  • Namra Joshi Assistant Professor, Department of Electrical Engineering, SVKM's Institute of Technology, Dhule, Maharashtra, India
  • Mohammad Arif Professor, Department of Computer Science and Engineering, Alliance University, Bengaluru, India – 562106
  • Mahesh Babu Kota Department of Electronics and Communication Engineering, Aditya University, Surampalem, Kakinada, India
  • Indhumathi R Assistant Professor, Department of Electrical and Electronics Engineering, M.Kumarasamy College of Engineering, Thalavapalayam, Karur, Tamilnadu, ‎India
  • Elangovan B Assistant Professor, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, Andhra Pradesh ‎‎- 522302‎.

About this article

DOI:

https://doi.org/10.14419/60apby38

Received:

15-04-2025

Accepted:

19-07-2025

Published:

27-07-2025

Views:

351

Downloads:

161
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Keywords:

Cloud Computing; VM Migration; CLOUD SIM; NetBeans; Skewness Algorithm; Automated Resource Management System

Abstract

Efficient resource management in cloud data centers is crucial for optimizing resource utilization while maintaining performance and energy ‎efficiency. This study presents the design and implementation of an automated dynamic resource management system that balances overload ‎avoidance and green computing. Overload avoidance is achieved by dynamically adjusting physical machine (PM) resources to meet virtual ‎machine (VM) demands, preventing performance degradation due to excessive resource contention. Simultaneously, energy efficiency is ‎ensured by minimizing the number of active PMs, turning off unused ones to conserve power. To enhance resource allocation, the concept ‎of skewness is introduced to measure the uneven utilization of server resources. By reducing skewness, overall server efficiency is ‎improved while addressing multi-dimensional resource constraints. The proposed system is implemented and evaluated using the ‎CLOUDSIM 2.0 simulation platform with NetBeans, demonstrating its effectiveness in optimizing resource allocation, preventing overload, ‎and reducing energy consumption in cloud environments.

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How to Cite

Swathi, T. ., Saravanan , S. ., Joshi , N. ., Arif , M. ., Kota , M. B. ., R, I., & B, E. . (2025). Effective Load Balancing on Servers Using Virtual Machines for ‎Cloud Computing Environment Using Green Computing and The Skewness Algorithm. International Journal of Basic and Applied Sciences, 14(3), 385-395. https://doi.org/10.14419/60apby38

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