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Efficient Resource Management in Cloud Environments: A Modified Feeding Birds Algorithm for VM Consolidation
Version 1
: Received: 7 June 2024 / Approved: 7 June 2024 / Online: 7 June 2024 (15:10:56 CEST)
A peer-reviewed article of this Preprint also exists.
Alsadie, D.; Alsulami, M. Efficient Resource Management in Cloud Environments: A Modified Feeding Birds Algorithm for VM Consolidation. Mathematics 2024, 12, 1845. Alsadie, D.; Alsulami, M. Efficient Resource Management in Cloud Environments: A Modified Feeding Birds Algorithm for VM Consolidation. Mathematics 2024, 12, 1845.
Abstract
Cloud data centers play a vital role in modern computing infrastructure, offering scalable resources for diverse applications. However, managing costs and resources efficiently in these centers has become a crucial concern due to the exponential growth of cloud computing. User applications exhibit complex behavior, leading to fluctuations in system performance and increased power usage. To tackle these obstacles, we propose the consolidation of virtual machines (VMs) to optimize resource utilization and reduce operational costs. This paper introduces a novel algorithm, leveraging the Modified Artificial Feeding Birds Algorithm (ModAFBA), to manage cost optimally in cloud data centers by reducing power usage while meeting service level agreements (SLAs). The ModAFBA algorithm, inspired by bird foraging behavior, dynamically adjusts solutions based on environmental changes. Comprehensive experimental evaluation demonstrates the superiority of the proposed algorithm in terms of power usage, migration count, and SLA compliance. Through this research, we aim to advance cost management and resource optimization in cloud data centers, providing a valuable tool for cloud service providers to enhance infrastructure efficiency and achieve cost savings.
Keywords
Cloud data centers; Virtual machine consolidation; power efficiency; Artificial Feeding Birds Algorithm; Cost management
Subject
Computer Science and Mathematics, Computer Science
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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