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Social Relation Predictive Model of Mobile Nodes in Internet of Things

机译:物联网中移动节点的社会关系预测模型

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摘要

With the development of Internet of Things, humans with smart multimedia devices are a new trend of mobile-aware service. This new mode of awareness will inevitable brings some challenges. Among them, the quantification of social relations is the basis of mobile-aware service, and it is an abstract psychological cognitive process, involving space, time and behaviour. Therefore, using social network theory, a novel quantization and predication model with multiple decision factors is proposed, in which multiple decision factors including location, call records, service and feedback factors. These factors are incorporated to reflect the complexity and uncertainty of social relations. Also, the weight distribution is set up by information entropy, and support vector machines optimized based genetic algorithm is used to predict the social relations of mobile nodes, which overcomes the shortage of traditional method, in which the weight is set up by subjective manners and has poor dynamic adaptability. Simulation results show that, cognitive model has better predictive accuracy and dynamic adaptability.
机译:随着物联网的发展,具有智能多媒体设备的人们是移动感知服务的新趋势。这种新的意识模式将不可避免地带来一些挑战。其中,社会关系的量化是移动感知服务的基础,它是一个抽象的心理认知过程,涉及空间,时间和行为。因此,利用社交网络理论,提出了一种具有多个决策因素的量化和预测模型,其中包括位置,通话记录,服务和反馈因素等多个决策因素。这些因素被合并以反映社会关系的复杂性和不确定性。此外,权重分布是通过信息熵来建立的,并且使用基于遗传算法优化的支持向量机来预测移动节点的社会关系,从而克服了传统方法的缺点,即通过主观的方式来建立权重。动态适应性差。仿真结果表明,认知模型具有较好的预测精度和动态适应性。

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