Underwater sensor network routing method based on multiple underwater autonomous vehicles

Abstract

The invention discloses an underwater sensor network routing method based on multiple underwater autonomous vehicles. The method comprises the steps of network initialization, data transmission, network restoration and the like. In the network initialization stage, a dynamic network hierarchical structure is constructed; the underwater common sensor nodes in the underwater sensor network are layered, so that a progressive gradient is formed, and a data packet can be transmitted to a corresponding underwater autonomous vehicle according to the hierarchical relationship of the underwater commonsensor nodes in a subsequent data transmission stage. In the data transmission stage, the underwater common sensor node sorts the transmission priorities of the candidate nodes according to the composite forwarding factors of the candidate nodes, and transmission coordination of the candidate node set is carried out based on the transmission priorities of the candidate nodes, so that data packet conflicts are avoided, and the network delay is reduced; in the network restoration stage, the network restoration model is utilized to carry out periodic restoration when the initial dynamic network hierarchical structure changes, so that the transmission performance of the underwater sensor network is improved.

Description

technical field [0001] The invention belongs to the technical field of underwater wireless sensor networks, in particular to an underwater sensor network routing method based on multiple underwater autonomous vehicles. Background technique [0002] Underwater sensor network is an important application of wireless sensor network under water. The underwater sensor network refers to the deployment of underwater sensor nodes with low energy consumption and a certain communication distance in the designated sea area, and the network is automatically established by using the self-organization ability of the nodes. These underwater sensor nodes have acoustic communication capabilities, while the sonobuoys floating on the surface have video and acoustic communication capabilities. The underwater sensor node transmits the acoustic signal to the sonobuoy on the water surface. After the sonobuoy receives it, it transmits it to the control center through the radio frequency signal, and...

AI Technical Summary

Problems solved by technology

The DBR protocol has good performance in a dense network, but in a sparse network, multiple forwarding nodes may transmit the same data packet, or the node cannot find a suitable next-hop forwarding node, resulting in information redundancy Sending and transmission delay of packets

The REBAR (Reliable and Energy Balanced Routing Algorithm) routing protocol invented by Chen J et al. proposes node mobility as a positive factor for balancing network energy consumption, which divides the network into two areas and defines one of them as the hotspot area around the convergence , and the other parts are common areas. The protocol will exchange the nodes in the two areas through the mobility of nodes, so as to balance the energy consumption between each node. However, this protocol needs to know the geographical location of each common node and the sink node clearly. Acquisition of geographic location information will increase network energy consumption and data transmission information to a certain extent.

Seokhoon Yoon et al. proposed an AUV-assisted routing protocol AURP (An AUV-Aided Underwater Routing Protocol). The node layering does not require location information, and the data is transmitted to the gateway node according to the layered information, and then collected by the AUV at a high rate at a short distance. data, and transport the data to the sink node, the impact of AUV collection path on network performance is considered in this paper, but the adaptability to dynamic topology is not strong, and the initiative of AUV is not fully utilized

However, no reports have been found on the routing method of underwater sensor networks based on multiple underwater autonomous vehicles.

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