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Trust-A ware Resource Provisioning for Meteorological Workflow in Cloud

机译:云中气象工作流的信任软件资源配置

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Cloud computing centers are becoming the predominant platform of offering high-performance computing services based on high-performance computers. However, enabling meteorological workflow that requires real-time response is still challenging due to uncertainty in the cloud, once the computing nodes in the cloud are down, the tasks deployed on the cloud will not be completed in time. To address this problem, an optimal cloud resource for the downtime tasks provisioning method (ODPM) is proposed by formulating a programming model. The ODPM method can select the appropriate migration strategy for the tasks on the compute node to achieve the shortest workflow completion time and load balancing of the compute center compute nodes. A large number of experimental are conducted to verify the benefits brought by ODPM.
机译:云计算中心正在成为基于高性能计算机提供高性能计算服务的主要平台。但是,由于云中的不确定性,启用需要实时响应的气象工作流仍然具有挑战性,一旦云中的计算节点发生故障,部署在云中的任务将无法及时完成。为了解决这个问题,通过制定编程模型,提出了用于停机任务供应方法(ODPM)的最佳云资源。 ODPM方法可以为计算节点上的任务选择适当的迁移策略,以实现最短的工作流完成时间和计算中心计算节点的负载平衡。进行了大量实验以验证ODPM带来的好处。

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