基于改进布谷鸟搜索算法对水质监测无线传感器部署的优化

doi:10.3969/j.issn.1004-1524.2020.05.18

浙江农业学报 ›› 2020, Vol. 32 ›› Issue (5): 897-903.DOI: 10.3969/j.issn.1004-1524.2020.05.18

基于改进布谷鸟搜索算法对水质监测无线传感器部署的优化

胡坚¹, 胡峰俊², 张红¹, 朱颖¹

1.浙江经贸职业技术学院信息技术系, 浙江杭州 310018;
2.浙江树人大学信息科技学院,浙江杭州310015

收稿日期:2019-11-04 出版日期:2020-05-25 发布日期:2020-05-29
作者简介:胡坚(1979—),男,浙江台州人,硕士,副教授,主要从事大数据技术与应用、机器学习与智能算法研究。E-mail:843877248@qq.com
基金资助:
国家自然科学基金 (51675490)

Optimization of wireless sensor network for water quality monitoring based on improved cuckoo search algorithm

HU Jian¹, HU Fengjun², ZHANG Hong¹, ZHU Ying¹

1. Information Technology Department, Zhejiang Institute of Economics and Trade, Hangzhou 310018, China;
2. College of Information and Science Technology, Zhejiang Shuren University, Hangzhou 310015, China

Received:2019-11-04 Online:2020-05-25 Published:2020-05-29

摘要/Abstract

摘要： 为解决传统传感器网络随机部署分布不均的问题,提出采用布谷鸟搜索算法(CS)进行节点部署优化。为改善CS算法的全局优化性能以提升传感器节点部署优化能力,受动量梯度下降法、均方根算法和Adam优化算法的启发,提出Momentum-CS、RMSprop-CS与Adam-CS三种改进算法,对CS算法中的步长控制量和淘汰概率进行优化调整。以网络覆盖率为优化目标,将3种算法用于长宽为100 m水域的水质监测无线传感器节点部署进行优化。仿真结果表明,Adam-CS算法能够在较少迭代次数获取更高的网络覆盖率,达到90.35%,对于指导水环境监测中无线传感器节点部署具有现实意义。

关键词: 无线传感器, 水质监测, 布谷鸟搜索算法, Adam优化

Abstract: In order to solve the problem of uneven distribution of random deployment of traditional sensor networks, cuckoo search algorithm (CS) was proposed to optimize node deployment. In order to improve the global optimization performance of CS algorithm and enhance the deployment optimization ability of sensor nodes, inspired by gradient descent with momentum, root mean square algorithm and Adam optimization algorithm, three improved algorithms, namely Momentum-CS, RMSprop-CS and Adam-CS, were proposed to optimize and adjust the step size control and elimination probability in CS algorithm. Taking network coverage as the optimization target, three algorithms were used to optimize the deployment of water quality monitoring wireless sensor nodes in water area with length and width of 100 meters. Simulation results showed that the Adam-CS algorithm could achieve a higher network coverage of 90.35% in fewer iterations, which was of practical significance for guiding the deployment of wireless sensor nodes in water environment monitoring.

Key words: wireless sensor, water quality monitoring, cuckoo optimization algorithm, Adam optimization

中图分类号:

S27
TP212

胡坚, 胡峰俊, 张红, 朱颖. 基于改进布谷鸟搜索算法对水质监测无线传感器部署的优化[J]. 浙江农业学报, 2020, 32(5): 897-903.

HU Jian, HU Fengjun, ZHANG Hong, ZHU Ying. Optimization of wireless sensor network for water quality monitoring based on improved cuckoo search algorithm[J]. , 2020, 32(5): 897-903.

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基于改进布谷鸟搜索算法对水质监测无线传感器部署的优化

Optimization of wireless sensor network for water quality monitoring based on improved cuckoo search algorithm

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