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EP-ADTA：用于水下无线传感器网络（UWSN）的基于边缘预测的自适应数据传输算法

EP-ADTA: Edge Prediction-Based Adaptive Data Transfer Algorithm for Underwater Wireless Sensor Networks (UWSNs).

作者信息

Wang Bin, Ben Kerong, Lin Haitao, Zuo Mingjiu, Zhang Fengchen

机构信息

College of Electronic Engineering, Naval University of Engineering, Wuhan 430033, China.

出版信息

Sensors (Basel). 2022 Jul 23;22(15):5490. doi: 10.3390/s22155490.

DOI:10.3390/s22155490
PMID:35897994
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9332410/
Abstract

The underwater wireless sensor network is an important component of the underwater three-dimensional monitoring system. Due to the high bit error rate, high delay, low bandwidth, limited energy, and high dynamic of underwater networks, it is very difficult to realize efficient and reliable data transmission. Therefore, this paper posits that it is not enough to design the routing algorithm only from the perspective of the transmission environment; the comprehensive design of the data transmission algorithm should also be combined with the application. An edge prediction-based adaptive data transmission algorithm (EP-ADTA) is proposed that can dynamically adapt to the needs of underwater monitoring applications and the changes in the transmission environment. EP-ADTA uses the end-edge-cloud architecture to define the underwater wireless sensor networks. The algorithm uses communication nodes as the agents, realizes the monitoring data prediction and compression according to the edge prediction, dynamically selects the transmission route, and controls the data transmission accuracy based on reinforcement learning. The simulation results show that EP-ADTA can meet the accuracy requirements of underwater monitoring applications, dynamically adapt to the changes in the transmission environment, and ensure efficient and reliable data transmission in underwater wireless sensor networks.

摘要

水下无线传感器网络是水下三维监测系统的重要组成部分。由于水下网络存在高误码率、高延迟、低带宽、能量有限以及高动态性等问题，实现高效可靠的数据传输非常困难。因此，本文认为仅从传输环境角度设计路由算法是不够的；数据传输算法的综合设计还应结合应用。提出了一种基于边缘预测的自适应数据传输算法（EP - ADTA），该算法能够动态适应水下监测应用的需求和传输环境的变化。EP - ADTA采用端 - 边缘 - 云架构来定义水下无线传感器网络。该算法以通信节点为代理，根据边缘预测实现监测数据的预测和压缩，动态选择传输路由，并基于强化学习控制数据传输精度。仿真结果表明，EP - ADTA能够满足水下监测应用的精度要求，动态适应传输环境的变化，并确保水下无线传感器网络中数据的高效可靠传输。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0373/9332410/28b465ce5d90/sensors-22-05490-g015.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0373/9332410/e7385eba43c9/sensors-22-05490-g011.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0373/9332410/11c9bb7fc4fd/sensors-22-05490-g013.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0373/9332410/ee9983022ec3/sensors-22-05490-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0373/9332410/10d4580e00aa/sensors-22-05490-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0373/9332410/e063de6174a3/sensors-22-05490-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0373/9332410/9a0108927fa2/sensors-22-05490-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0373/9332410/9b93f175367e/sensors-22-05490-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0373/9332410/e7385eba43c9/sensors-22-05490-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0373/9332410/fdb07d490456/sensors-22-05490-g012.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0373/9332410/28b465ce5d90/sensors-22-05490-g015.jpg

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