| Underwater wireless sensor networks(UWSN)is a kind of underwater monitoring system consisting of nodes capable of sensing underwater information,storing and processing information data,and communicating through underwater acoustic signals.Since many countries are paying more attention on the ocean resources,UWSN has become a research focus.At present,the research about UWSN involves the following aspects such as node deployment,node localization,time synchronization,energy-efficient strategies,underwater security and so on.And the node deployment is not only closely related to the network monitoring quality,but also the basis of the various subsequent protocols and algorithms.Therefore,how to design the node deployment algorithm in an effective and reasonable way has become the basic problem for the UWSN design.The deployment algorithms for UWSN can be classified into random deployment and deterministic deployment.As to the deterministic deployment,it can be classified into the static deployment,movement-limited deployment and movement-free deployment according to the assumption on the node movement ability.The technology such as the AUV makes it possible that the node can move freely towards any desired direction and lay a foundation for many UWSN node deployment algorithms where the nodes can move freely.However,there exist some defaults in this kind of algorithm,for example,this kind of algorithm usually consider how to improve the network coverage rate,ignoring the optimization of other performances,such as network connectivity rate,network deployment energy consumption and network lifetime.Thus,this thesis conducts the following researches:(1)A node non-uniform deployment based on clustering algorithm for UWSN is proposed because optimizing network connectivity rate and network lifetime is difficult for the existing node non-uniform deployment algorithms under the premise of improving the network coverage rate for UWSN.The heterogeneous communication ranges of nodes are determined during node clustering,moreover,the concept of aggregate contribution degree is defined and the nodes with lower aggregate contribution degrees are used to substitute the dying nodes.Simulation results show that the proposed algorithm can achieve a better network coverage rate and network connectivity rate,as well as decrease the total movement distance of nodes and prolong the network lifetime.(2)Existing node deployment algorithms for UWSN are nearly unable to improve the network coverage rate under the premise of ensuring the full network connectivity and do not optimize the communication and move energy consumption during the deployment.Hence,a node deployment algorithm based on connected dominating set(CDS)is proposed.After randomly sowing the nodes in 3D monitoring underwater space,disconnected nodes move to the Sink node until the network achieves full connectivity.The Sink node then performs centralized optimization to determine the CDS and adjusts the locations of dominated nodes.Simulation results show that the proposed algorithm can achieve high coverage rate while ensuring full connectivity and decrease the communication and movement energy consumption during deployment.(3)Existing node deployment algorithms for UWSN are nearly unable to improve the network coverage rate and network connectivity rate during the network operation under the premise of considering the node drift,so a node redeployment based on stratified connected tree algorithm is proposed.Firstly,nodes can avoid moving outside the monitored water space by self-test and adjustment.Then,the network is stratified to become a connected tree with the Sink node as the root.Finally,the Sink node adjusts the locations of leaf nodes in the stratified connected tree to improve the network coverage rate,along with consideration of network connectivity rate and node movement energy consumption.Simulation results show that the proposed algorithm can make nodes stay in the monitored water space to the greatest extent,and make the network achieve a better coverage rate and connectivity rate during the network operation,as well as decrease the node movement energy consumption during the network redeployment,thus prolongs the network lifetime. |
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