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

Abstract

The invention discloses a mobile data collection method for three-dimensional UASNs (underwater acoustic sensor networks) based on probability neighborhood cover sets. The method comprises the steps of establishing a probabilistic communication model of the 3D underwater acoustic sensor networks; establishing the probability neighborhood cover sets as stay points of an AUV based on the established probabilistic communication model of the 3D underwater acoustic sensor networks; planning a data collection path of the AUV based on the probability neighborhood cover sets and collecting data of a whole network. According to the method, through adoption of the probabilistic communication model, the data collection distance can flexibly adjusted according to probability demands; data collection is carried out by employing the AUV, the energy consumption of the sensor nodes for data transmission can be effectively reduced, and the network lifetime is prolonged; through establishment of the probability neighborhood cover sets, the AUV does not need to traverse all the sensor nodes, the data collection finishing time is effectively shortened, and the data delay is reduced; and through change of a value of a data transmission success rate rho and a data transmission number of turns, an effective solution for balancing information gain and data delay is provided.

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 coverage sets. 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...

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

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