AUV movement data collection algorithm in underwater sensor network based on data prediction

Abstract

The invention discloses an AUV mobile data collecting method in an underwater sensing network based on data prediction, comprising that AUV uses a centralized algorithm to initialize a maximum neighbor node density cluster, uses SVR to fit and predict the acquired data and establish a prediction model, and updates the cluster according to the trend similarity degree of the predicted model; the AUVand the corresponding cluster save the same prediction model synchronously; in a data collection process, the access collection of the clusters is skipped and the prediction model is directly used for prediction; when the prediction model of the corresponding cluster is larger than a preset maximum tolerance error threshold or delay sensitive threshold, a update request is sent immediately; bidirectional search is used in order to find the current position of the AUV and a change is notified; and the AUV re-plans the remaining path to obtain a new prediction model. Through data prediction, the AUV traversal path length is reduced to reduce the energy consumption and collection delay of the AUV, the amount of data size of the entire network is reduced, the energy consumption of some nodesis reduced, and the overall network performance is improved.

Description

technical field [0001] The invention belongs to the technical field, and in particular relates to an AUV mobile data collection algorithm in an underwater sensor network based on data prediction. Background technique [0002] With the continuous development of Underwater Wireless Sensor Networks (UWSNs), we can obtain more and more specific information about oceans or rivers through diverse underwater applications. For example, monitor the temperature and sulfur dioxide concentration changes in the submarine volcanic area through the underwater sensor network, so as to predict the state of the volcano and give an early warning of the possible eruption state; and monitor the military area to prevent the invasion of enemy submarines and warships. However, the underwater sensor network is different from the terrestrial sensor network. Under water, the radio signal attenuation increases with the increase of frequency and is much greater than that on land, which is a fatal injury...

AI Technical Summary

Problems solved by technology

[0008] In order to solve the problem of excessive collection delay caused by the use of AUV mobile data collection in the underwater sensor network, and the continuous depreciation of information value over time, the present invention proposes an underwater sensor network based on data prediction, taking into account the existing data collection schemes that reduce delay In the AUV mobile data collection algorithm, the SVR algorithm is used to fit and predict the data, and the clusters are updated according to the forecast trend. The AUV and the corresponding clusters have the same prediction model, and the access to these clusters is skipped during the data collection process. Directly use the prediction model to make predictions, thus shortening the AUV traversal path length to speed up the collection process

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