Fault-Tolerant Scheduling for Hybrid Real-Time Tasks Based on CPB Model in Cloud
Fault-Tolerant Scheduling for Hybrid Real-Time Tasks Based on CPB Model in Cloud
复制标题
基于CPB模型的云端混合实时任务容错调度
DOI：
10.1109/access.2018.2810214
复制
发表时间：
2018
期刊：
影响因子：
3.9
通讯作者：
Zhou Wen
中科院分区：
文献类型：
--
作者：
Han Haoran;Bao Weidong;Zhu Xiaomin;Feng Xiaosheng;Zhou Wen
云正在成为混合实时任务的重要平台。为了提高云的可靠性，云的容错性成为一个关键问题。然而，传统的容错机制的复杂性和特殊性不能满足云的容错需求。为了解决这个问题，我们提出了一种新的容错调度算法名为ARCHER的混合任务在云中。ARCHER具有三个显著的特点：1）它结合了传统的主/备模型和检查点技术，可以灵活地确定任务备份副本的执行时间，从而大大提高了资源利用率，产生更多的时隙来执行尽可能多的任务; 2）采用任务分类机制，实现对不同类型任务和虚拟机的精确调度，减少云的响应时间; 3）采用时隙开发机制、任务转发机制和任务转换机制，实现了高资源利用率。我们进行了广泛的模拟，以评估性能的ARCHER比较它与四个基线算法。实验结果表明，ARCHER在保证容错的同时，有效提高了云的资源利用率。
Clouds are becoming a very important platform for hybrid real-time tasks. To enhance the reliability of cloud, fault tolerance of cloud becomes a critical issue. However, the complexities and specialties of traditional fault-tolerant mechanisms cannot meet the fault-tolerant requirements of clouds. To address this issue, we propose a novel fault-tolerant scheduling algorithm named ARCHER for hybrid tasks in cloud. ARCHER has three significant characteristics: 1) it integrates the traditional primary/backup model and checkpoint technology which can flexibly determine the execution time of the backup copies of tasks, so it greatly enhances the resource utilization and produces more time slots to execute tasks as many as possible; 2) it employs task classification mechanism to realize precise scheduling for different types of tasks and virtual machines, which reduces the response time of clouds; and 3) it uses time slot exploiting mechanism, task forward mechanism, and task transform mechanism to achieve high-resource utilization. We conduct extensive simulations to evaluate the performance of ARCHER by comparing it with four baseline algorithms. The experimental results show that ARCHER can effectively improve the resource utilization of cloud while guaranteeing fault tolerance.