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Robust Resource Allocation in Weather Data Processing Systems

机译:天气数据处理系统中的鲁棒资源分配

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Reliability of weather data processing systems is of prime importance to ensure the efficient operation of space-based weather monitoring systems. This work defines a heterogeneous weather data processing system that is susceptible to uncertainties in data set arrival times. The resource allocation must be robust with respect to these uncertainties. The tasks to be executed by the data processing system are classified into three broad categories: telemetry, tracking and control (high priority); data processing (medium priority); and data research (low priority). The high priority tasks must be completed before considering medium and low priority tasks. The goal of this research is to find a resource allocation that minimizes makespan of the high priority tasks, and to find a mapping that maximizes a function of the completion time and priority of the medium and low priority tasks. Different heuristic techniques to find near optimal solutions are studied, and their performance is evaluated.
机译:天气数据处理系统的可靠性是最重要的,以确保基于空间的天气监测系统的有效运行。这项工作定义了一种异质天气数据处理系统,该系统易受数据集到达时间的不确定性的影响。关于这些不确定性的资源分配必须具有稳健。数据处理系统执行的任务分为三个广泛类别:遥测,跟踪和控制(高优先级);数据处理(中等优先级);和数据研究(低优先级)。在考虑中期和低优先级任务之前,必须完成高优先级任务。本研究的目标是找到一种资源分配,可最大限度地减少高优先级任务的MapSpan,并找到一个最大化介质和低优先级任务的完成时间和优先级的函数的映射。研究了不同的启发式技术,用于找到附近的最佳解决方案,并评估其性能。

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