IoT (Internet of Things) information flow perception is the foundation of the IoT architecture and plays an important role. Providing cloud services on demand is one of the key issues and core features of cloud services in the IoT information flow perception. Firstly, we study the mixed logic dynamics (MLD) modeling method of IoT information flow awareness, and use IoT sensor nodes, controlled nodes, and coordination nodes to describe system application scenarios, and use automata for internal information transmission. Secondly, an open queuing method based on large-scale information flow perception modeling and network delay analysis method is proposed. By analyzing the end-to-end delay of the node path and the average delay analysis of the whole queuing network, the open queuing is obtained. Aiming at the characteristics of distributed data of information flow perception in the IoT, a priority-based queuing network is proposed to model and analyze the aggregation nodes based on embedded multi-core SoC(System on Chip), which greatly improves the performance of embedded multi-core SoC.

中文翻译：

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云服务物联网信息流感知建模与优化

IoT（Internet of Things）信息流感知是物联网架构的基础，发挥着重要作用。按需提供云服务是物联网信息流感知云服务的关键问题和核心特征之一。首先，研究物联网信息流感知的混合逻辑动力学（MLD）建模方法，利用物联网传感器节点、受控节点和协调节点来描述系统应用场景，并使用自动机进行内部信息传输。其次，提出了一种基于大规模信息流感知建模和网络时延分析方法的开放排队方法。通过分析节点路径的端到端时延以及整个排队网络的平均时延分析，得到开放排队。针对物联网中信息流感知数据分布式的特点，提出一种基于优先级的排队网络，对基于嵌入式多核SoC（System on Chip）的汇聚节点进行建模和分析，大大提高了嵌入式系统的性能。多核 SoC。