E2SVM:在云数据中心的电效SLA意识的虚拟机整合方法
Vaneet Kumar1, Aleem Ali1, Payal Mittal2
1Department of Computer Science and Engineering, Chandigarh University, Gharuan, India.
PloS one
|June 10, 2024
概括
本研究介绍了云数据中心虚拟机 (VM) 整合的新算法. 它通过智能选择虚拟机进行迁移来降低能源消耗,并最大限度地减少违反服务水平协议 (SLA) 的情况.
科学领域:
- 计算机科学 计算机科学
- 环境可持续性 环境可持续性
- 云计算 云计算 云计算 云计算
背景情况:
- 云数据中心消耗大量能源,挑战环境可持续性.
- 像虚拟机 (VM) 整合这样的能源管理解决方案可以降低性能并违反服务级别协议 (SLA).
研究的目的:
- 提出一种新的VM整合算法,平衡能源效率和SLA遵守.
- 解决 VM 选择和迁移中常规算法的局限性.
主要方法:
- 开发了用于VM整合的E2SVM算法.
- E2SVM从超载的服务器中选择具有高负载波动和最小资源使用的虚拟机.
- 虚拟机被放置在正常加载的服务器上,使用稳定性指数,防止服务器使用不足.
主要成果:
- 与最小迁移时间政策相比,最大能耗下降了12.9%.
- 使用中等绝对偏差用于超载检测,观察到SLA违规减少了47%.
结论:
- 拟议的E2SVM算法有效地减少了云数据中心的能源浪费.
- 这种方法保持了较低的SLA违规,显示了对现实世界应用的希望.
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