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通过进化调度方法优化云计算环境中的完成时间和资源利用率。

Optimizing makespan and resource utilization in cloud computing environment via evolutionary scheduling approach.

机构信息

Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia.

Department of Information Technology, College of Computer, Qassim University, Buraydah, Saudi Arabia.

出版信息

PLoS One. 2024 Nov 22;19(11):e0311814. doi: 10.1371/journal.pone.0311814. eCollection 2024.

DOI:10.1371/journal.pone.0311814
PMID:39576796
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11584144/
Abstract

As a new computing resources distribution platform, cloud technology greatly influenced society with the conception of on-demand resource usage through virtualization technology. Virtualization technology allows physical resource usage in a way that will enable multiple end-users to have similar hardware infrastructure. In the cloud, many challenges exist on the provider side due to the expectations of clients. Resource scheduling (RS) is the most significant nondeterministic polynomial time (NP) hard problem in the cloud, owing to its crucial impact on cloud performance. Previous research found that metaheuristics can dramatically increase CC performance if deployed as scheduling algorithms. Therefore, this study develops an evolutionary algorithm-based scheduling approach for makespan optimization and resource utilization (EASA-MORU) technique in the cloud environment. The EASA-MORU technique aims to maximize the makespan and effectively use the resources in the cloud infrastructure. In the EASA-MORU technique, the dung beetle optimization (DBO) technique is used for scheduling purposes. Moreover, the EASA-MORU technique balances the load properly and distributes the resources based on the demands of the cloud infrastructure. The performance evaluation of the EASA-MORU method is tested using a series of performance measures. A wide range of comprehensive comparison studies emphasized that the EASA-MORU technique performs better than other methods in different evaluation measures.

摘要

作为一种新的计算资源分配平台，云技术通过虚拟化技术以按需使用资源的概念极大地影响了社会。虚拟化技术允许以一种方式使用物理资源，使多个最终用户拥有类似的硬件基础设施。在云中，由于客户的期望，提供商方面存在许多挑战。资源调度 (RS) 是云中最重要的非确定性多项式时间 (NP) 难题，因为它对云性能有至关重要的影响。以前的研究发现，如果将元启发式算法部署为调度算法，它们可以显著提高 CC 的性能。因此，本研究在云环境中开发了一种基于进化算法的调度方法，用于最大完成时间和资源利用优化 (EASA-MORU)。EASA-MORU 技术旨在最大化完成时间并有效地利用云基础设施中的资源。在 EASA-MORU 技术中，使用蜣螂优化 (DBO) 技术进行调度。此外，EASA-MORU 技术根据云基础设施的需求合理平衡负载并分配资源。使用一系列性能指标对 EASA-MORU 方法的性能评估进行了测试。广泛的综合比较研究强调，EASA-MORU 技术在不同的评估指标下比其他方法表现更好。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b08/11584144/5295d3dc84b1/pone.0311814.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b08/11584144/d0cb5a55b84b/pone.0311814.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b08/11584144/f2d29d043208/pone.0311814.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b08/11584144/ccd16c427919/pone.0311814.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b08/11584144/2ffac7fbe160/pone.0311814.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b08/11584144/93e0977b5ad4/pone.0311814.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b08/11584144/04e584d20772/pone.0311814.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b08/11584144/edf170569198/pone.0311814.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b08/11584144/ca10c0962c17/pone.0311814.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b08/11584144/5295d3dc84b1/pone.0311814.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b08/11584144/d0cb5a55b84b/pone.0311814.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b08/11584144/f2d29d043208/pone.0311814.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b08/11584144/ccd16c427919/pone.0311814.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b08/11584144/2ffac7fbe160/pone.0311814.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b08/11584144/93e0977b5ad4/pone.0311814.g005.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b08/11584144/edf170569198/pone.0311814.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b08/11584144/ca10c0962c17/pone.0311814.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8b08/11584144/5295d3dc84b1/pone.0311814.g009.jpg

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