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基于水下能量传播模型、并行传输和复制计算的改进型LEACH协议在水下声学传感器网络中的应用

Improved LEACH Protocol Based on Underwater Energy Propagation Model, Parallel Transmission, and Replication Computing for Underwater Acoustic Sensor Networks.

作者信息

Tian Kun, Zhou Chang, Zhang Jun

机构信息

School of Electronic and Information Engineering, South China University of Technology, Guangzhou 510641, China.

出版信息

Sensors (Basel). 2024 Jan 16;24(2):556. doi: 10.3390/s24020556.

Abstract

Underwater acoustic sensor networks (UASNs) are critical to a range of applications from oceanographic data collection to submarine surveillance. In these networks, efficient energy management is critical due to the limited power resources of underwater sensors. The LEACH protocol, a popular cluster-based protocol, has been widely used in UASNs to minimize energy consumption. Despite its widespread use, the conventional LEACH protocol faces challenges such as an unoptimized cluster number and low transmission efficiency, which hinder its performance. This paper proposes an improved LEACH protocol for cluster-based UASNs, where the cluster number is optimized with an underwater energy propagation model to reduce energy consumption, and a transmission scheduling algorithm is also employed to achieve conflict-free parallel data transmission. Replication computing is introduced to the LEACH protocol to reduce the signaling in the clustering and data transmission phases. The simulation results show that the proposed protocol outperforms several conventional methods in terms of normalized average residual energy, average number of surviving nodes, average round when the first death node occurs, and the number of packets received by the base station.

摘要

水下声学传感器网络(UASN)对于从海洋学数据收集到潜艇监视等一系列应用至关重要。在这些网络中,由于水下传感器的电源资源有限,高效的能量管理至关重要。LEACH协议是一种流行的基于簇的协议,已在UASN中广泛使用以最小化能量消耗。尽管其被广泛使用,但传统的LEACH协议面临诸如簇数量未优化和传输效率低等挑战,这阻碍了其性能。本文针对基于簇的UASN提出了一种改进的LEACH协议,其中使用水下能量传播模型优化簇数量以降低能量消耗,并且还采用了一种传输调度算法来实现无冲突的并行数据传输。将复制计算引入LEACH协议以减少聚类和数据传输阶段的信令。仿真结果表明,所提出的协议在归一化平均剩余能量、存活节点的平均数量、第一个死亡节点出现时的平均轮数以及基站接收的数据包数量方面优于几种传统方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d15a/10818593/cb4268547af9/sensors-24-00556-g001.jpg

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