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基于距离预测与多准则决策的水声网络分层路由协议

张振儒 杜秀娟 田晓静 李冲 韩多亮

计算机应用研究2025,Vol.42Issue(1):262-268,7.
计算机应用研究2025,Vol.42Issue(1):262-268,7.DOI:10.19734/j.issn.1001-3695.2024.06.0182

基于距离预测与多准则决策的水声网络分层路由协议

Distance prediction and multi-criteria decision based layering routing for underwater acoustic networks

张振儒 1杜秀娟 2田晓静 1李冲 1韩多亮1

作者信息

  • 1. 青海师范大学计算机学院,西宁 810008||青海省物联网重点实验室,西宁 810008
  • 2. 青海师范大学计算机学院,西宁 810008||青海省物联网重点实验室,西宁 810008||藏语智能信息处理及应用国家重点实验室,西宁 810008
  • 折叠

摘要

Abstract

Underwater sensor nodes may move with the water current,resulting in a highly dynamic network topology,which brings about challenges for the routing in underwater acoustic network(UAN).To cope with the challenges of node mobility and energy efficiency in UAN,this paper proposed a distance prediction and multi-criteria decision based layering routing for underwater acoustic networks(DMD-LR).To predict the distance between nodes,this paper presented a gray Markov inter-node distance prediction model based on an improved gray prediction model.According to the prediction results based on the gray Markov distance prediction model,it provided an effective neighbor node determination rule.Further,it proposed a grey re-lational analysis model based on multi-criteria decision to calculate the grey relational degree(GRD)of neighbor nodes,and selected the neighbor node with the highest GRD as the optimal next hop.It conducted extensive experiments with the NS3 net-work simulation simulator to evaluate the performance of the DMD-LR protocol.The results show that the DMD-LR protocol has great advantages in improving packet delivery rate,reducing end-to-end delay,and lowering total energy consumption compared with the LEER,DBR,VBF,LR-NMP,and IATLR protocols.

关键词

距离预测/灰色马尔可夫/多准则决策/水声网络/路由协议

Key words

distance prediction/grey Markov model/multi-criteria decision making/underwater acoustic networks/rou-ting protocol

分类

信息技术与安全科学

引用本文复制引用

张振儒,杜秀娟,田晓静,李冲,韩多亮..基于距离预测与多准则决策的水声网络分层路由协议[J].计算机应用研究,2025,42(1):262-268,7.

基金项目

国家自然科学基金资助项目(61962052) (61962052)

青海省物联网重点实验室资助项目 (2024-ZJ-929) (2024-ZJ-929)

计算机应用研究

OA北大核心

1001-3695

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