4.7 Article

Construction and simulation of performance evaluation index system of Internet of Things based on cloud model

期刊

COMPUTER COMMUNICATIONS
卷 153, 期 -, 页码 177-187

出版社

ELSEVIER
DOI: 10.1016/j.comcom.2020.02.016

关键词

Internet of Things; Performance evaluation; Probability density function; Gray relation; Cloud model

资金

  1. Science and Technology Program projecT of Shandong University of Higher Education, Study on the effective information extraction of artificial intelligence in cerebrovascular imaging [J18KA335]

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Due to the lack of corresponding scientific evaluation standards and effective evaluation methods for the overall performance of the Internet of Things system, the Internet of Things industry and the market are in a chaotic state, and the quality of various products is uneven. It is difficult for users to select a more suitable application system, which seriously restricts the development process of the industrialization of Internet of Things technology. Therefore, it is very necessary for us to conduct research on the performance evaluation methods of IoT systems. In this paper, the performance of IoT system is selected as the performance evaluation index of the system, and the evaluation system is constructed. The performance evaluation method of the Internet of Things system based on the cloud model is proposed. The comprehensive evaluation of the reliability of the IoT system for the cloud model will be based on the AHP. Based on the combination of attribute decision-making methods, a comprehensive evaluation method based on indicators is proposed, and the system's indicator model is established. The reliability of the Internet of Things system can be comprehensively evaluated by the value of the indicators. Secondly, the probability density function of tracking error is studied, and its optimal probability density distribution is given by optimal control. Based on the optimal probability density distribution, the performance evaluation index of the system is constructed. In order to compare the current probability density function with the reference probability density function, the tracking error function is first vector, then the performance evaluation index is constructed by gray correlation, and the general steps of performance evaluation based on this index are given. Finally, the effectiveness of the proposed system performance evaluation algorithm is verified by simulation comparison. The data processing and experimental simulation are used to achieve the purpose of evaluating the performance of the Internet of Things system.

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