Mobile Data Collection Method for 3D UASNS Based on Probabilistic Neighborhood Grid

Abstract

The invention discloses a mobile data gathering method of 3D UASNs (underwater acoustic sensor networks) based on probability neighbor grids. The method comprises the following steps: according to the feature of a 3D underwater acoustic sensor network, constructing a 3D underwater acoustic sensor network probabilistic communication model in comprehensive consideration of sound wave attenuation, ocean current surface activity, turbulence noise, wind, thermal noise and like factors; dividing the network into the probability neighbor grids based on the constructed 3D underwater acoustic sensor network probabilistic communication model; planning a data gathering path of AUV based on the probability neighbor grids, and then gathering data in the whole network. Therefore, the method disclosed by the invention has the beneficial effects as follows: the data gathering distance can be flexibly adjusted according to the probability demand through the adoption of the probabilistic underwater acoustic communication model; the AVU is used for gathering data so as to effectively reduce the energy consumption of a sensor node for data transmission, and prolong the network life; the network is divided into small grids, the data gathering can be finished only needing the AUV to traverse the center positions of the grids, and the method can be effectively applied to the unknown underwater acoustic sensor network for node deployment information; a solution scheme for effectively balancing information gain and data delay is provided through the change of the value of the data transmission success rate p and the data transmission rounds.

Description

technical field [0001] The invention belongs to the field of underwater acoustic sensor networks, in particular to a method for collecting mobile data of three-dimensional UASNs based on probabilistic neighborhood grids. Background technique [0002] Underwater data collection is of great significance to the application of underwater acoustic sensor networks (UASNs). Whether it is the monitoring and management of the underwater environment or the monitoring and early warning of underwater disasters, people need to use UASNs to collect and obtain Perceive the interest information in the monitoring area, and then analyze, process, store and mine the information, and finally make a reasonable and effective decision. In many applications of UASNs, data collection requires the transmission of a large amount of sensing data, and the transmission of a large amount of sensing data in the network will generate a large amount of communication overhead. In addition, since node energy ...

AI Technical Summary

Problems solved by technology

[0011] 1) The design of most underwater acoustic sensor network data collection schemes is based on the ideal deterministic underwater acoustic communication model, but in practical applications, the data transmission success rate of the underwater acoustic channel is attenuated with the distance, when the data transmission fails , data collection will not be complete;

[0012] 2) The cluster-based data collection method will increase the energy consumption of cluster head nodes, which will eventually lead to uneven energy consumption of the network and reduce the life of the network;

[0013] 3) Most mobile-assisted data collection methods assume that sensor nodes are deployed on the same plane, which cannot be effectively applied to 3D water environments;

[0014] 4) Highly dependent on node deployment information, for networks with unknown node deployment information, the data collection method cannot be realized

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