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    曹 洁, 曾国荪, 钮 俊, 许金超. 云环境下可用性感知的并行任务调度方法[J]. 计算机研究与发展, 2013, 50(7): 1563-1572.
    引用本文: 曹 洁, 曾国荪, 钮 俊, 许金超. 云环境下可用性感知的并行任务调度方法[J]. 计算机研究与发展, 2013, 50(7): 1563-1572.
    Cao Jie, Zeng Guosun, Niu Jun, Xu Jinchao. Availability-Aware Scheduling Method for Parallel Task in Cloud Environment[J]. Journal of Computer Research and Development, 2013, 50(7): 1563-1572.
    Citation: Cao Jie, Zeng Guosun, Niu Jun, Xu Jinchao. Availability-Aware Scheduling Method for Parallel Task in Cloud Environment[J]. Journal of Computer Research and Development, 2013, 50(7): 1563-1572.

    云环境下可用性感知的并行任务调度方法

    Availability-Aware Scheduling Method for Parallel Task in Cloud Environment

    • 摘要: 云计算是一种新兴的计算模式,倡导一切皆服务.云计算由于能够共享分布在世界各地的计算资源,在大规模计算和数据存储中越来越受到重视.云计算是当前IT工业界、学术界研究的热点领域,云环境中的资源可用性已成为云计算不可忽视的问题.对于云计算,当处理器的处理速度不同,不是一直可用于计算时,可用性成为设计和发展云计算系统的关键需求.根据并行任务图及树形云平台的结构特点,分别讨论了影响并行任务可用性需求和计算资源可用性保障的关键因素,给出一种可用性的量化计算公式.并且通过感知任务“可用性需求”和计算资源“可用性保障”,实现可用性匹配,提出了两种可用性感知的调度算法Afsa和Agsa.模拟实验表明该算法能够改善云环境中资源可用性和可靠性,对提高任务调度的成功率具有实际意义.

       

      Abstract: Cloud computing is a newly emerging computing paradigm that advocates supplying users everything as a service. Cloud computing becomes more and more popular in large scale computing and data store recently due to it enables the sharing of computing resources that are distributed all over the world. Nowdays, cloud computing is a hot research area in IT industries and in academic institutes. Particularly, the problem of resource availability cannot be ignored in cloud environment. High availability is a key requirement in the design and development of cloud computing systems where processors operate at different speeds and are not continuously available for computation. This paper addresses the main factors of availability requirement for parallel tasks and the influencing factors of availability support for computational resources based on the graph structure of parallel task and tree cloud platform. We present the formulas to quantify the availability. Through being aware of availability, we realize the availability matching between availability requirement and availability support, and develop two availability-aware scheduling algorithms, that are Afsa and Agsa. The simulation experimental results show that such algorithms can effectively enhance the resource availability and reliability in cloud environment. It is significant to improve the success rate of parallel task scheduling in practice.

       

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