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Modeling Situational Awareness in Network Centric Systems

机译:以网络为中心的系统中的态势感知建模

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Modeling Situation awareness (SA) in NCO/NCW environments is inherently challenging due to the complexity of the underlying network, highly dynamic nature of processes, and the need for real time analysis. In this paper, we present a performance model for SA using the Network Centric Operations Performance & Prediction (NCO-PP) framework, an established framework for analyzing and predicting performance of NCO/NCW networks. In this paper, we continue to formulate a realistic model that represents dynamism in both the information and network spaces and also their effects on each other. We validate our model via simulations that compare the performance of SA under various information sharing and filtering paradigms. We provide and define a number of relevant performance metrics for SA and show with experimental results that modeling the dynamism in the network lead to superior SA. We also show that the performance of the SA can be significantly improved with proactive resource allocation that takes into account the real time predictions of the future states of the network and the environment.
机译:由于基础网络的复杂性,过程的高度动态性以及实时分析的需要,在NCO / NCW环境中建模态势感知(SA)固有地具有挑战性。在本文中,我们使用网络中心操作性能和预测(NCO-PP)框架提出了SA的性能模型,该框架是用于分析和预测NCO / NCW网络性能的已建立框架。在本文中,我们将继续构建一个现实的模型,该模型在信息空间和网络空间以及它们之间的相互影响中代表动态。我们通过仿真比较了各种信息共享和过滤范例下SA的性能,从而验证了我们的模型。我们为SA提供并定义了许多相关的性能指标,并通过实验结果表明,对网络中的动态性进行建模可以产生出众的SA。我们还表明,考虑到网络和环境的未来状态的实时预测,可以通过主动分配资源来显着提高SA的性能。

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