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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:

34

期数:

2024年03期

页码:

89-95

栏目:

移动与物联网络

出版日期:

2024-03-10

文章信息/Info

Title:

Research on WSN Coverage Based on Improved Snake Optimizer Algorithm

文章编号:

1673-629X(2024)03-0089-07

作者:

李 振; 冯 锋*

宁夏大学 信息工程学院,宁夏 银川 750021

Author(s):

LI Zhen; FENG Feng*

School of Information Engineering,Ningxia University,Yinchuan 750021,China

关键词:

无线传感器网络; 节点覆盖; 蛇优化; Halton 序列; 异性相吸

Keywords:

wire sensor network; node coverage; snake optimizer algorithm; Halton sequence; opposites attraction

分类号:

TP393. 0

DOI:

10. 3969 / j. issn. 1673-629X. 2024. 03. 014

摘要:

为了有效提高无线传感器网络( WSN) 部署时的覆盖效果,增加节点间的连通性,提出一种基于改进蛇优化算法的节点多目标部署优化策略。 在种群初始化阶段,针对蛇优化算法的随机种群初始化分布不均匀的问题,引入 Halton 序列初始化策略对种群个体进行初始化,并使种群各个节点具有一定区间范围内的随机性特征,既保证了初始化种群个体内均匀分布,又使得个体间具有多样性;在开发阶段,提出了一种新的觅食策略取代原本觅食阶段的方法,能够促使个体快速跳出局部最优;在开发阶段的交配模式中,提出了一种异性吸引策略取代交配策略,使算法具备更强的全局探索与开发能力。 然后,将所提算法与基本的蛇优化算法、单阶段改进的蛇优化算法以及其他改进优化算法进行对比。 仿真结果表明,不同阶段的改进策略对改进算法产生了不同程度的影响。 此外,改进后的算法在无线传感器网络覆盖优化性能方面也优于其他改进的优化部署算法。

Abstract:

In order to effectively improve the coverage effect and increase the connectivity among nodes when wireless sensor network( WSN) are deployed,a multi-objective deployment optimization strategy of nodes based on the improved snake optimization algorithmis proposed. In the population initialization phase,the Halton sequence initialization strategy is introduced to initialize the population individuals for the uneven distribution of the random population initialization of the snake optimization algorithm,and to make each node of　the population have the randomness characteristics within a certain interval,which not only ensures the uniform distribution within the initialized population individuals,but also makes the diversity among individuals. In the development phase, a new foraging strategy isproposed to replace the original foraging phase,which can prompt individuals to quickly jump out of the local optimum. In the matingmode of the development phase,a heterosexual attraction strategy is proposed to replace the mating strategy,so that the algorithm has astronger global exploration and exploitation capability. Then,we will compare the proposed algorithm with the basic snake optimizationalgorithm,the single-stage improved snake optimization algorithm and other improved optimization algorithms. The simulation resultsshow that the improvement strategies in different stages have different degrees of influence on the improved algorithm. In addition,theimproved algorithm outperforms other improved optimized deployment algorithms in terms of wireless sensor network coverageoptimization performance.

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更新日期/Last Update: 2024-03-10