在云计算环境中,使用动态时间量子进行实时不对称的爆发长度过程的增强圆形连锁.
Most Fatematuz Zohora1, Fahiba Farhin2, M Shamim Kaiser3
1Computer Science and Engineering, Bangladesh Army International University of Science and Technology, Cumilla, Bangladesh.
PloS one
|August 15, 2024
概括
这项研究介绍了用于云计算任务调度的增强圆形罗宾算法. 动态量子时间方法最大限度地减少了等待和周转时间,优于现有方法.
科学领域:
- 计算机科学 计算机科学
- 云计算 云计算 云计算 云计算
- 算法优化的算法优化
背景情况:
- 云计算提供动态的按需服务,需要高效的任务调度以获得最佳性能.
- 虚拟机资源配置对于云环境至关重要,任务调度起着关键作用.
- 轮算法是资源分配的常见方法,旨在最大限度地减少响应和周转时间.
研究的目的:
- 为云计算系统中任务调度引入一种全新的,增强的轮回罗宾算法.
- 解决云环境中动态任务执行和资源共享的挑战.
- 通过动态调整量子时间来改进现有的调度算法.
主要方法:
- 开发了一种新的,增强的循环罗宾算法,可以动态生成和更新量子时间.
- 算法考虑了过程的数量及其爆发长度,用于动态量子时间计算.
- 该方法是为实时环境而设计的,可以处理不对称的爆发时间分布,减轻车队效应.
主要成果:
- 拟议的算法与现有增强的轮回组合方法相比,表现出更高的性能.
- 实现了平均等待时间 (15.77%) 和上下文切换 (20.68%) 的显著减少.
- 有效地管理具有不对称爆发时间的任务,避免车队效应.
结论:
- 增强的Round Robin调度算法是最佳的,并且非常适合云计算环境.
- 动态量子时间调整为任务安排提供了更好的方法.
- 该算法在云系统中提供了更高效,更平衡的资源分配.
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