Enhanced sine cosine algorithm based node deployment optimization of wireless sensor network

doi:10.11772/j.issn.1001-9081.2018112282

Journal of Computer Applications ›› 2019, Vol. 39 ›› Issue (7): 2035-2043.DOI: 10.11772/j.issn.1001-9081.2018112282

• Network and communications • Previous Articles Next Articles

Enhanced sine cosine algorithm based node deployment optimization of wireless sensor network

HE Qing1,2, XU Qinshuai1,2, WEI Kangyuan1,2

1. College of Big Data and Information Engineering, Guizhou University, Guiyang Guizhou 550025, China;
2. Guizhou Provincial Key Laboratory of Public Big Data(Guizhou University), Guiyang Guizhou 550025, China

Received:2018-11-15 Revised:2018-12-24 Online:2019-07-10 Published:2019-01-23
Supported by:
This work is partially supported by the Guizhou Provincial Science and Technology Project ([2018]3002), the Open Project of Guizhou Provincial Key Laboratory of Public Big Data (2017BDKFJJ004), the Guizhou Provincial Education Department Project for Young Scientific and Technical Talents (KY[2016]124), the Training Project of Guizhou University ([2017]5788).

基于改进正弦余弦算法的无线传感器节点部署优化

何庆^1,2, 徐钦帅^1,2, 魏康园^1,2

1. 贵州大学大数据与信息工程学院, 贵阳 550025;
2. 贵州省公共大数据重点实验室(贵州大学), 贵阳 550025

通讯作者: 何庆
作者简介:何庆(1982-),男,贵州贵阳人,副教授,博士,主要研究方向:人工智能、无线传感器网络;徐钦帅(1994-),男,山东滕州人,硕士研究生,主要研究方向:智能计算、无线传感器网络;魏康园(1991-),女,陕西渭南人,硕士研究生,主要研究方向:数据挖掘、智能计算。
基金资助:
贵州省科技计划项目重大专项（黔科合重大专项字[2018]3002）；贵州省公共大数据重点实验室开放课题项目（2017BDKFJJ004）；贵州省教育厅青年科技人才成长项目（黔科合KY字[2016]124）；贵州大学培育项目（黔科合平台人才[2017]5788）。

Abstract

Abstract:

In order to improve the performance of Wireless Sensor Network (WSN), a node deployment optimization method based on Enhanced Sine Cosine Algorithm (ESCA) was proposed. Firstly, hyperbolic sine regulatory factor and dynamic cosine wave weight coefficient were introduced to balance the global exploration and local exploitation capability of the algorithm. Then, a mutation strategy based on Laplacian and Gaussian distribution was proposed to avoid the algorithm falling into local optimum. The experimental results of benchmark function optimization show that, compared with gravitational search algorithm, whale optimization algorithm, basic Sine Cosine Algorithm (SCA) and improved algorithms, ESCA has better convergence accuracy and convergence speed. Finally, ESCA was applied to WSN node deployment optimization. The results show that, compared with enhanced particle swarm optimization algorithm, extrapolation artificial bee colony algorithm, improved grey wolf optimization algorithm and self-adaptive chaotic quantum particle swarm algorithm, ESCA has improved the coverage rate by 1.55 percentage points, 7.72 percentage points, 2.99 percentage points and 7.63 percentage points respectively, and achieves the same target precision with fewer nodes.

Key words: Wireless Sensor Network (WSN), node deployment, Sine Cosine Algorithm (SCA), hyperbolic sine regulatory factor, Laplace distribution

摘要：

为了提高无线传感器网络（WSN）的性能，提出了一种基于改进正弦余弦算法（ESCA）的节点部署优化方法。首先，引入双曲正弦调节因子和动态余弦波权重系数，以平衡算法的全局探索与局部开发能力；然后，提出了一种基于拉普拉斯和高斯分布的变异策略，避免算法陷入局部最优。对于基准函数的优化实验结果表明，ESCA相比引力搜索算法、鲸鱼优化算法、基本正弦余弦算法（SCA）及其改进算法具有更高的收敛精度和收敛速度。最后，将ESCA应用于WSN节点部署优化，结果表明其优化覆盖率相比改进粒子群优化算法、外推人工蜂群算法、改进灰狼优化算法和自适应混沌量子粒子群算法分别提高了1.55个百分点、7.72个百分点、2.99个百分点和7.63个百分点，用更少节点便可达到相同目标精度。

关键词: 无线传感器网络, 节点部署, 正弦余弦算法, 双曲正弦调节因子, 拉普拉斯分布

CLC Number:

TP183
TP393

HE Qing, XU Qinshuai, WEI Kangyuan. Enhanced sine cosine algorithm based node deployment optimization of wireless sensor network[J]. Journal of Computer Applications, 2019, 39(7): 2035-2043.

何庆, 徐钦帅, 魏康园. 基于改进正弦余弦算法的无线传感器节点部署优化[J]. 计算机应用, 2019, 39(7): 2035-2043.

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Enhanced sine cosine algorithm based node deployment optimization of wireless sensor network

基于改进正弦余弦算法的无线传感器节点部署优化

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