Citation

Ullah, Arif and Abdul Razak, Siti Fatimah and Mrhari, Amine and Yogarayan, Sumendra and Kazmi, Syeda Hina Mazhar (2025) Improving Load Balancing Efficiency in Cloud Data Centers Through Hybrid Grey Wolf with Cat Swarm Optimization. Informatica (Slovenia), 49 (28). pp. 121-136. ISSN 0350-5596

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Abstract

An effective resource management strategy that anticipates server resource utilization and appropriately distributes the load is recommended in order to address these problems and enhance data center performance. By reducing the number of servers in use, facilitating virtual machine migrations, and optimizing resource utilization, it helps save power. To reduce the likelihood of service level agreement (SLA) violations and performance degradation caused by either oveloded or under loaded servers and virtual machines. Resources for software applications can now be dynamically altered as needed thanks to the growth of cloud computing. Since better resource consumption can lead to increased scalability as well as significant cost and energy savings, effective resource management is crucial in cloud computing. The flexibility of cloud resources allows clients to dynamically increase and decrease their resource demands over time. However, predefined virtual machine sizes and variable resource requirements result in underutilization of resources, load imbalances, and high power consumption. The goal of this research is to develop a hybrid technique by combining Grey Wolf with algorithms. The hybridization processes take place in the Grey Wolf portion, when the Cat Swarm initialization process takes the place of the startup phase. The virtual machine (VM) section's data selection is enhanced by this substitution. The Grey Wolf and Cat Swarm algorithms are two examples of optimization algorithms. The evaluation criteria that are used are makespan, throughput, degree of imbalance, and turnaround time with degree of imbalance. The recommended approach outperforms alternative algorithms in each of these metrics. The proposed hybrid strategy resulted in 0.3% increase overall performance. Potential directions for future research inclu

Item Type:	Article
Uncontrolled Keywords:	Degree of imbalance, makespan, throughput, turnaround time, virtual machine
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Nor Afiqah Mohd Adnan
Date Deposited:	10 Nov 2025 00:33
Last Modified:	10 Nov 2025 02:53
URII:	http://shdl.mmu.edu.my/id/eprint/14787

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