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基于分层连通树的水下传感器网络节点重新部署算法

Node Redeployment Algorithm Based on Stratified Connected Tree for Underwater Sensor Networks.

作者信息

Liu Jun, Jiang Peng, Wu Feng, Yu Shanen, Song Chunyue

机构信息

College of Automation, Hangzhou Dianzi University, Hangzhou 310018, China.

State Key Laboratory of Industrial Control Technology, Institute of Industrial Process Control, Zhejiang University, Hangzhou 310027, China.

出版信息

Sensors (Basel). 2016 Dec 24;17(1):27. doi: 10.3390/s17010027.

Abstract

During the underwater sensor networks (UWSNs) operation, node drift with water environment causes network topology changes. Periodic node location examination and adjustment are needed to maintain good network monitoring quality as long as possible. In this paper, a node redeployment algorithm based on stratified connected tree for UWSNs is proposed. At every network adjustment moment, self-examination and adjustment on node locations are performed firstly. If a node is outside the monitored space, it returns to the last location recorded in its memory along straight line. Later, the network topology is stratified into a connected tree that takes the sink node as the root node by broadcasting ready information level by level, which can improve the network connectivity rate. Finally, with synthetically considering network coverage and connectivity rates, and node movement distance, the sink node performs centralized optimization on locations of leaf nodes in the stratified connected tree. Simulation results show that the proposed redeployment algorithm can not only keep the number of nodes in the monitored space as much as possible and maintain good network coverage and connectivity rates during network operation, but also reduce node movement distance during node redeployment and prolong the network lifetime.

摘要

在水下传感器网络(UWSN)运行期间,节点随水环境的漂移会导致网络拓扑结构发生变化。需要定期进行节点位置检测和调整,以尽可能长时间地保持良好的网络监测质量。本文提出了一种基于分层连通树的UWSN节点重新部署算法。在每个网络调整时刻,首先对节点位置进行自我检测和调整。如果一个节点超出了监测空间,它将沿直线返回其内存中记录的上一个位置。随后,通过逐层广播就绪信息,将网络拓扑分层为以汇聚节点为根节点的连通树,这可以提高网络连通率。最后,汇聚节点综合考虑网络覆盖率、连通率以及节点移动距离,对分层连通树中的叶节点位置进行集中优化。仿真结果表明,所提出的重新部署算法不仅能够在网络运行期间尽可能多地保留监测空间内的节点数量,保持良好的网络覆盖率和连通率,还能在节点重新部署期间减少节点移动距离,延长网络寿命。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dcd5/5298600/242d1e370687/sensors-17-00027-g001.jpg

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