计算机科学 ›› 2026, Vol. 53 ›› Issue (6A): 250600229-10.doi: 10.11896/jsjkx.250600229

• 网络&通信 • 上一篇    下一篇

多源异构传感器双层优化部署方法

成清1,2,3, 黄一川1,2, 罗志浩1,2   

  1. 1 国防科技大学系统工程学院 长沙 410073
    2 国防科技大学大数据与决策国家级重点实验室 长沙 410073
    3 湖南先进技术研究院 长沙 410006
  • 出版日期:2026-06-16 发布日期:2026-06-12
  • 通讯作者: 成清(sgggps@163.com)
  • 基金资助:
    国家自然科学基金(72301290)

Two-layer Optimization Deployment Method for Multi-source Heterogeneous Sensors

CHENG Qing1,2,3, HUANG Yichuan1,2 , LUO Zhihao1,2   

  1. 1 School of Systems Engineering,National University of Defense Technology,Changsha 410073,China
    2 Laboratory for Big Data and Decision,National University of Defense Technology,Changsha 410073,China
    3 Hunan Advanced Technology Research Institute,Changsha 410006,China
  • Published:2026-06-16 Online:2026-06-12
  • About author:CHENG Qing,born in 1986,associate professor.His main research interests include knowledge reasoning and multi-objective optimization.
  • Supported by:
    National Natural Science Foundation of China(72301290).

摘要: 边防区域作为军事斗争的核心区域,部署多源异构传感器网络(WSNs)可实现全天候态势感知。针对大规模的多源异构传感器部署应用,传感器部署需要综合平衡传感器网络整体效能与传感器部署成本。针对此问题,提出一种基于双层优化的多源异构传感器部署框架,构建上层以制造成本、部署成本及维护成本最小化为目标,下层综合网络覆盖率、可靠性及生命周期的多目标优化模型,并且设计双种群改进NSGA-II算法进行双层优化模型求解,通过种群分治策略与四分位距消解机制优化Pareto前沿分布,从而解决双层优化模型的嵌套结构求解困难问题。最后针对模型的应用问题,采用仿真实验验证了模型的有效性与算法优越性。

关键词: 传感器优化部署, 网络覆盖率, 改进NSGA-II算法, 双层优化

Abstract: As a core area of military struggle,the border defense region can achieve all-weather situation awareness by deploying multi-source heterogeneous sensor networks(WSNs).For large-scale multi-source heterogeneous sensor deployment applications,sensor deployment needs to comprehensively balance the overall performance of the sensor network and the cost of sensor deployment.To address this issue,this paper proposes a multi-source heterogeneous sensor deployment framework based on double-layeroptimization,constructing an upper layer with the objective of minimizing manufacturing cost,deployment cost,and maintenance cost,and a lower layer with a multi-objective optimization model that integrates network coverage,reliability,and life cycle.Moreover,a two-population improved NSGA-II algorithm is designed to solve the double-layer optimization model,optimizing the Pareto front distribution through a population divide-and-conquer strategy and an interquartile range resolution mechanism,thereby solving the difficulty in solving the nested structure of the double-layer optimization model.Finally,to verify the application of the model,simulation experiments are conducted to demonstrate the effectiveness of the model and the superiority of the algorithm.

Key words: Sensor optimal deployment, Network coverage rate, Improved NSGA-II algorithm, Two-layer optimization

中图分类号: 

  • TP393
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