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Dynamic Level Task Scheduling Algorithm based on Risk Estimation Model in Grid Computing

机译:基于网格计算风险估计模型的动态级任务调度算法

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In a heterogeneous distributed Grid system, machines and network failures are inevitable and can have an adverse effect on applications execution on the system, therefore the objective of task scheduling is not only to minimize the makespan of applications, but also to reduce risks for application execution failures. A new algorithm named by Risk-DLS algorithm will be proposed, which will combine a risk estimation model of resources with the DLS algorithm through an improved equation of dynamic level. The simulation shows that when choosing reasonable parameters, Risk-DLS algorithm is better than DLS algorithm in makespan, at the same time, it can also reduce the adverse effect due to uncertain environment of grid computing.
机译:在异构分布式网格系统中,机器和网络故障是不可避免的并且可以对系统执行的应用程序产生不利影响,因此任务调度的目标不仅可以最小化应用程序的Mapspan,而且还可以降低应用程序执行的风险失败。将提出一种由风险-DLS算法命名的新算法,这将通过改进的动态级别与DLS算法将资源的风险估计模型与DLS算法组合。仿真结果表明,在选择合理的参数时,风险-DLS算法比Mepespan中的DLS算法更好,同时也可以降低由于网格计算的不确定环境而降低不利影响。

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