A Data Set Accuracy Weighted Random Forest Algorithm for IoT Fault Detection Based on Edge Computing and Blockchain

【Author】 Zhang, Wenbo; Wang, Jiaxing; Han, Guangjie; Huang, Shuqiang; Feng, Yongxin; Shu, Lei

【Source】IEEE INTERNET OF THINGS JOURNAL

【影响因子】10.238

【Abstract】The continuously increasing number of connected smart devices has led to the emergence of a crucial fault detection challenge to the Internet of Things (IoT). In this study, we aim to identify a method for the effective detection of faults in IoT devices. An IoT network model is first established, and a data edge verification mechanism based on blockchain is proposed; the blockchain is used to ensure that the data cannot be tampered with, and their accuracy is verified using the edge. Finally, a data set accuracy weighted random forest based on particle swarm optimization is proposed. The simulation results demonstrate that the proposed detection algorithm is both effective and efficient.

【Keywords】Logic gates; Internet of Things; Blockchain; Fault detection; Cloud computing; Image edge detection; Distributed databases; Blockchain; edge computing; fault detection; Internet of Things (IoT); PSO-DAWRF

【发表时间】2021 44607

【收录时间】2022-01-02

【文献类型】

【主题类别】

--