从数据到决策:将情景信息需求推到网络边缘

J. Preden, J. Kaugerand, E. Suurjaak, S. Astapov, L. Motus, R. Pahtma
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引用次数: 30

摘要

在保持最佳资源利用的同时获得高水平的态势感知变得越来越重要,特别是在不对称战争的背景下,信息优势对于保持对对手的优势至关重要。从ISR系统获得足够水平的态势信息取决于传感器的能力,以及根据当前信息需求适当提示传感器的能力,以及利用收集到的数据和适当的数据处理方法的能力。将数据应用于决策方法来管理传感器系统的行为,有助于优化传感器资产的使用,同时提供所需级别的态势信息。本文提出的方法将数据到决策方法与雾计算范式相结合,其中计算被推到网络的边缘。这样就可以利用传感器系统产生的大数据,同时保持可管理的带宽资源需求。我们建议采用系统的系统方法来组装ISR系统,其中单个系统具有高水平的自主性和执行必要计算任务的计算资源。为了便于战术应用中传感器系统的组合,采用了主动中间件ProWare。本文中介绍的工作是作为欧洲防务局IN4STARS项目的一部分进行的,在该项目的背景下,正在构建传感器解决方案的实施,该解决方案通过建立雾计算范式和利用数据决策概念,促进传感器之间的在线传感器提示和协作。
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Data to decision: pushing situational information needs to the edge of the network
Obtaining a high level of situation awareness while maintaining optimal utilization of resources is becoming increasingly important, especially in the context of asymmetric warfare, where information superiority is crucial for maintaining the edge over the opponent. Obtaining an adequate level of situational information from an ISR system is dependent on sensor capabilities as well as the ability to cue the sensors appropriately based on the current information needs and the ability to utilize the collected data with suitable data processing methods. Applying the Data to Decision approach for managing the behavior of sensor systems facilitates optimal use of sensor assets while providing the required level of situational information. The approach presented in the paper combines the Data to Decision approach with the Fog Computing paradigm, where the computation is pushed to the edge of the network. This allows to take advantage of Big Data potentially generated by the sensor systems while keeping the resource requirements in terms of bandwidth manageable. We suggest a System of Systems approach for assembling the ISR system, where individual systems have a high level of autonomy and the computational resources to perform the necessary computation tasks. To facilitate a composition of a System of Systems of sensors for tactical applications the proactive middleware ProWare is applied. The work presented in the paper has been conducted as part of the European Defense Agency project IN4STARS, in the context of which an implementation of a sensor solution is being built, which facilitates on-line sensor cueing and collaboration between sensors by building upon the Fog Computing paradigm and utilizing the Data to Decision concepts.
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