Link quality prediction method for wireless sensor network

Abstract

The invention discloses a link quality prediction method for a wireless sensor network, comprising the following steps: S1, de-noising link quality parameters by adopting a Kalman filter algorithm, standardizing the link quality parameters by adopting a maximum and minimum method, and dividing the link quality level by adopting a fuzzy C-means clustering algorithm; and S2, training with an XGBoostalgorithm to obtain a link quality prediction model, and predicting the link quality level at next moment through the prediction model. The invention provides a link quality prediction method for a wireless sensor network based on XGBoost in consideration of dynamic change of the link quality of the wireless sensor network, which can effectively predict the link quality at the next moment and improve the throughput of the network, thereby improving the data forwarding efficiency of the network, and providing a basis for selecting a communication link for an upper layer routing protocol. In addition, the method has the advantages of prolonging the network lifetime and saving node energy.

Description

technical field [0001] The invention relates to the technical field of wireless sensors, in particular to a method for predicting link quality of a wireless sensor network. Background technique [0002] Wireless sensor networks (Wireless Sensor Networks, WSNs) are composed of a large number of cheap miniature sensor nodes deployed in the monitoring area, and form a multi-hop self-organizing network through wireless communication. information about the perceived object and send it to the observer. Sensors, sensing objects and observers constitute the three elements of a wireless sensor network. Sensor nodes are limited in terms of energy, communication, computing, and storage, and the deployment environment is usually complex and changeable with various sources of interference, resulting in unreliable quality of communication links between nodes. The link quality prediction mechanism is the basis of topology control, routing protocols and mobility management, which can impr...

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Problems solved by technology

[0003] In related technologies, the assessment and prediction methods of WSNs link quality mainly include prediction methods based on link characteristics and probability estimation, but both methods have the problem of low data forwarding efficiency, which affects the link quality at the next moment. quality prediction

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