通过进化调度方法,优化云计算环境中的产量和资源利用率
Faten K Karim1, Sara Ghorashi1, Salem Alkhalaf2
1Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia.
PloS one
|November 22, 2024
概括
本研究介绍了一种基于演进算法的调度方法,用于云计算中的 makespan 优化和资源利用 (EASA-MORU). 这种新的技术通过优化资源配置和负载平衡来提高云计算性能.
科学领域:
- 计算机科学 计算机科学
- 云计算 云计算 云计算
- 人工智能的人工智能
背景情况:
- 云计算通过虚拟化提供按需资源访问,为多个用户提供共享硬件基础设施.
- 资源调度 (RS) 是云环境中一个关键的NP-hard挑战,显著影响整体性能.
- 当应用到调度算法时,Metaheuristics在改善云计算 (CC) 性能方面表现有希望.
研究的目的:
- 开发一种基于进化算法的调度方法,用于在云环境中进行 makespan 优化和资源利用 (EASA-MORU).
- 通过高效的资源配置和负载平衡来提高云基础设施的性能.
- 解决云计算中的NP硬资源调度问题.
主要方法:
- 该研究提出了EASA-MORU技术,利用虫优化 (DBO) 算法来规划资源.
- 采用DBO技术,优化云基础架构中的产品范围和资源利用率.
- 该方法侧重于根据动态云需求平衡负载和分配资源.
主要成果:
- 与现有方法相比,EASA-MORU技术在产品优化和资源利用方面表现出卓越的性能.
- 综合性比较研究验证了EASA-MORU技术在各种性能指标上的有效性.
- 该方法有效地平衡负载,并根据云基础设施需求分配资源.
结论:
- 欧亚航天局-MORU技术为云计算中的资源调度挑战提供了有效的解决方案.
- 拟议的方法通过优化产量和资源利用来显著提高云计算性能.
- 虫优化 (DBO) 算法被证明是云资源调度的一个可行的元启发学.
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