基于分布式智能地球传感器网络的数据采集系统的计算机仿真结果

A. Materukhin, A. A. Maiorov, Oleg O. Gvozdev
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引用次数: 0

摘要

数据采集系统的建模与仿真一直是数据采集系统设计过程中的一个重要阶段。基于分布式智能地理传感器网络的数据采集系统是一种很有前途的数据采集系统。这项研究的目的是开发一种方法,根据其基本组件延迟的统计特性来评估数据采集系统的可扩展性潜力。为了模拟整个系统的延迟,作者开发了一个系统模型,以一组连贯的元素的形式影响通过它们的消息,主要是通过在传递中引入延迟。为了量化模型参数,开发了相应的软件工具。该软件工具包是使用NumPy和SimPy库用Python 3编程语言实现的。报告作者提出的方法可以减少使用各种算法确定已开发系统中空间谓词值的有效性的先验不确定性,并可以研究没有精确分析数学描述的数据采集系统中的过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Results of Computer Simulation of Data Acquisition Systems Based on Distributed Smart Geosensor Networks
Modeling and simulation of data acquisition systems has always been and remains an important stage in the process of their design. One of the promising classes of data acquisition systems is data acquisition systems based on distributed smart geosensor networks. The aim of the study was to develop a method for assessing the scalability potential of a data acquisition system based on the statistical properties of the latency of its basic components. To simulate the latency of the entire system, authors developed a system model in the form of a coherent set of elements that affect the messages passing through them, mainly by introducing delays in their passage. To quantify the model parameters, the corresponding software tools were developed. The software toolkit was implemented in the Python 3 programming language using the NumPy and SimPy libraries. The approach proposed by the authors of the report allows reducing the a priori uncertainty of the effectiveness of using various algorithms for determining the values of spatial predicates in the developed system and to study processes in the data acquisition system for which there is no exact analytical mathematical description.
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