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Forecasting capacity available for processing workloads in a networked computing environment

机译:预测可用于处理网络计算环境中的工作负载的容量

摘要

Embodiments of the present invention provide an approach for forecasting a capacity available for processing a workload in a networked computing environment (e.g., a cloud computing environment). Specifically, aspects of the present invention provide service availability for cloud subscribers by forecasting the capacity available for running or scheduled applications in a networked computing environment. In one embodiment, capacity data may be collected and analyzed in real-time from a set of cloud service providers and/or peer cloud-based systems. In order to further increase forecast accuracy, historical data and forecast output may be post-processed. Data may be post-processed in a substantially continuous manner so as to assess the accuracy of previous forecasts. By factoring in actual capacity data collected after a forecast, and taking into account applications requirements as well as other factors, substantially continuous calibration of the algorithm can occur so as to improve the accuracy of future forecasts and enable functioning in a self-learning (e.g., heuristic) mode.
机译:本发明的实施例提供了一种用于预测可用于在网络计算环境(例如,云计算环境)中处理工作量的容量的方法。具体地,本发明的方面通过预测在网络计算环境中可用于运行或调度的应用的容量来为云订户提供服务可用性。在一个实施例中,可以从一组云服务提供商和/或基于对等云的系统中实时收集和分析容量数据。为了进一步提高预测准确性,可以对历史数据和预测输出进行后处理。可以以基本上连续的方式对数据进行后处理,以便评估先前预测的准确性。通过将预测后收集的实际容量数据考虑在内,并考虑到应用程序要求以及其他因素,可以对算法进行基本连续的校准,从而提高未来预测的准确性并实现自我学习(例如,启发式)模式。

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