CRFTS:以集群为中心和基于预订的可容错调度策略,以提高云计算中的质量
Sheikh Umar Mushtaq1, Sophiya Sheikh2, Ajay Nain1
1School of computer applications ,Lovely Professional University, Jalandhar-Delhi, G.T. Road, Phagwara, 144411, Punjab, India.
Scientific reports
|September 1, 2025
概括
本研究介绍了聚类和预订容错调度 (CRFTS) 以优化云资源利用和任务完成时间. 通过主动检测VM故障和改进任务分配,CRFTS提高了系统可靠性,并减少了生产时间.
科学领域:
- 云计算
- 分布式系统
- 资源管理
背景情况:
- 在不断发展的云环境中,有效的资源利用,任务安排和故障耐受性至关重要.
- 优化任务执行时间 (makespan),运营费用,负载分配和资源利用需要高效的VM任务映射.
研究的目的:
- 为云环境引入新的调度策略和容错机制.
- 提出聚类和预订容错调度 (CRFTS) 模型,以提高服务质量.
主要方法:
- 使用心跳机制实施主动VM故障检测.
- 开发基于预订的故障宽容框架,以实现不间断的服务提供.
- 优化对虚拟机的任务分配,以提高资源利用率和缩短完成时间.
主要成果:
- 与HEFT,FTSA-1,DBSA,E-HEFT,LB-HEFT,BDHEFT,HO-SSA和MOTSWAO等现有方法相比,CRFTS在制造范围 (高达51.2%) 和平均资源利用率 (高达26.3%) 显著改善.
- 该模型增强了系统可靠性,并优化了 QoS 参数.
结论:
- 拟议的CRFTS模型有效地解决了云任务调度和故障容忍方面的挑战.
- 提供优化云性能,资源利用和服务可靠性的强大解决方案.
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