Resource-optimizing adaptation for big data applications

Holger Eichelberger, Klaus Schmid
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引用次数: 2

Abstract

The resource requirements of Big Data applications may vary dramatically over time, depending on changes in the context. If resources should not be defined for the maximum case, but available resources are mostly static, there is a need to adapt resource usage by modifying the processing behavior. The QualiMaster project researches such an approach for the analysis of systemic risks in the financial markets.
面向大数据应用的资源优化适应
随着时间的推移,大数据应用的资源需求可能会发生巨大变化,这取决于环境的变化。如果不应该为最大情况定义资源,但可用资源大多是静态的,则需要通过修改处理行为来调整资源使用情况。QualiMaster项目研究了一种分析金融市场系统性风险的方法。
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