基于铀尾矿库核素监测的WSN粒子群优化路由算法

doi:10.16265/j.cnki.issn1003-3033.2023.10.1772

中国安全科学学报 ›› 2023, Vol. 33 ›› Issue (10): 207-213.doi: 10.16265/j.cnki.issn1003-3033.2023.10.1772

基于铀尾矿库核素监测的WSN粒子群优化路由算法

周子翔¹(), 余修武¹^,²^,^**(), 彭威¹, 刘永³

¹ 南华大学资源环境与安全工程学院,湖南衡阳 421001
² 湖南省铀尾矿库退役治理技术处理研究中心,湖南衡阳 421001
³ 深圳大学物理与光电工程学院,广东深圳 518000

收稿日期:2023-04-12 修回日期:2023-07-14 出版日期:2023-10-28
通讯作者:
**余修武(1976—),男,江西九江人,博士,教授,主要从事无线传感器网络与安全智能监测方面的研究。E-mail:yxw2008xy@163.com。
作者简介:
周子翔 (1998—),男,广东茂名人,硕士研究生,主要研究方向为无线传感器网络路由、信息安全。E-mail:1572217429@qq.com。
余修武教授
刘永教授
基金资助:
国家自然科学基金资助(11875164); 湖南省市联合自然科学基金资助(2021JJ50093)

WSN particle swarm optimization routing algorithm based on nuclide monitoring of uranium tailings pond

ZHOU Zixiang¹(), YU Xiuwu¹^,²^,^**(), PENG Wei¹, LIU Yong³

¹ School of Resource & Environment and Safety Engineering, University of South China, Hengyang Hunan 421001, China
² Hunan Engineering Research Center for Uranium Tailings Decommission and Treatment, Hengyang Hunan 421001, China
³ College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen Guangdong 518000, China

Received:2023-04-12 Revised:2023-07-14 Published:2023-10-28

摘要/Abstract

摘要：

为提高铀尾矿库无线传感器网络(WSN)现有路由算法的网络寿命,提出一种基于铀尾矿库核素监测的WSN粒子群优化路由算法(EBPSO)。首先,在簇头(CH)选举阶段,考虑传感器节点的能量、簇内节点距离、CH到基站的距离等参数,利用粒子群优化(PSO)算法选出最合理的CH,并将筛选出来的CH节点应用于铀尾矿库核素监测组建WSN;其次,在数据传输阶段,提出转发节点的选择方法;然后,用能量阈值重分簇方案来减少能量消耗;最后,对比基于PSO优化模糊C均值的分簇路由算法(POFCA)、低功耗自适应分簇(LEACH)以及高效非均匀分簇算法(EEUC)性能。结果表明:在网络生命周期上,EBPSO算法比POFCA、LEACH、EEUC分别提升1.7%、24.7%、9.2%。EBPSO算法能够延长网络生命周期,适用于铀尾矿库核素监测应用场景。

关键词: 铀尾矿库, 核素监测, 无线传感器网络(WSN), 粒子群优化(PSO), 路由算法

Abstract:

A energy-balanced clustering algorithm for WSN based on PSO (EBPSO) for uranium tailings storage nuclide monitoring has been proposed to extend the network lifespan of existing WSN. Firstly, in the cluster head(CH) election stage, the particle swarm optimization algorithm was used to select the most reasonable CH. Taking into account parameters such as sensor node energy, distance between CH and distance between CH and base stations, the most reasonable CH nodes were selected and applied to uranium tailings pond nuclide monitoring, thus forming a wireless sensor network. Secondly, at the data transmission stage, a technique for selecting forwarding nodes was proposed. Then, to reduce energy consumption, an energy threshold re-clustering strategy was applied. Finally, the performance of clustering routing algorithm based on PSO algorithm optimized fuzzy C-means (POFCA), low energy adaptive clustering hierarchy(LEACH), and energy-efficient unequal clustering(EEUC) method were compared. The simulation test results demonstrate that compared with POFCA, LEACH, and EEUC, the network lifetime of EBPSO algorithm is increased by 1.7%, 24.7% and 9.2% respectively. It successfully extends the network lifespan and is ideal for the application situation of uranium tailings pond nuclide monitoring.

Key words: uranium tailings pond, radionuclide monitoring, wireless sensor network(WSN), particle swarm optimization(PSO), routing algorithm

周子翔, 余修武, 彭威, 刘永. 基于铀尾矿库核素监测的WSN粒子群优化路由算法[J]. 中国安全科学学报, 2023, 33(10): 207-213.

ZHOU Zixiang, YU Xiuwu, PENG Wei, LIU Yong. WSN particle swarm optimization routing algorithm based on nuclide monitoring of uranium tailings pond[J]. China Safety Science Journal, 2023, 33(10): 207-213.

图/表 11

图1

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表1

试验参数设置

参数名称	节点数目	BS位置	网络规模	最大轮数r_max	数据信息/bit	控制信息/bit	a
取值	100	(50,50)	100 m×100 m	2 000	4 000	200	0.5
参数名称	节点初始能量E₀/J	$ε f s$ /pJ·(bit^-1·m^-4)	$ε m p$ /pJ·(bit^-1·m^-4)	E_t/(nJ·bit^-1)	d₀/m	C₁	C₂
取值	0.6	10	0.0013	50	87	2	2

表1

图6

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图10

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基于铀尾矿库核素监测的WSN粒子群优化路由算法

WSN particle swarm optimization routing algorithm based on nuclide monitoring of uranium tailings pond

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