The Reliability of IoT Networks With Characteristics of Abnormal Induced Signals

Abstract

The abnormal nodes of the Internet of Things (IoT) are closely related to the reliability of the network, but it is always a difficulty to predict the characteristics of the induced signals that threaten reliability. In this article, a feature analysis method for the abnormal signal inducing the unreliable anomaly in IoT based on chaos attractor is proposed to make phase space reconstruction of the abnormal signal that the nodes of IoT can induce unreliability. The phase space structure is constructed by the sequence of abnormal signals. The chaotic attractor is used to analyze the phase space characteristics and reflect the phase space characteristics of unreliable signals induced by the network from the geometric point of view. The mutual information method is used to solve the time delay of the unreliable abnormal signal of IoT, calculate the embedding dimension, find out the chaotic attractors under different characteristics, and judge the reliability change characteristics by analyzing the chaotic attractors. The experimental results show that the method has a better time slot consumption, throughput, and idle energy indexes. Furthermore, our experiments show that the chaos attractor method can effectively predict the reliability trend of IoT, and better predict the reliability anomalies of IoT.