计算机科学 ›› 2017, Vol. 44 ›› Issue (Z6): 319-321.doi: 10.11896/j.issn.1002-137X.2017.6A.073

• 网络与通信 • 上一篇    下一篇

无线传感器网络节点的自定位技术研究

熊志利,瞿少成   

  1. 黄冈师范学院电子信息学院 黄冈438000;华中师范大学物理科学与技术学院 武汉430079,华中师范大学物理科学与技术学院 武汉430079
  • 出版日期:2017-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家自然科学基金项目(61673190/F030101),华中师范大学中央高校探索创新项目(CCNU15A02060),湖北省教育厅科学研究项目(B2016207),黄冈师范学院科技创新团队项目(201613603),黄冈师范学院“信息与通信”重点学科建设项目,黄冈师范学院电子信息工程虚拟仿真实验项目资助

Self Localization Technology of Wireless Sensor Network Node

XIONG Zhi-li and QU Shao-cheng   

  • Online:2017-12-01 Published:2018-12-01

摘要: 首先, 总结和分析 无线传感网络节点自定位的基本原理、分类,得到自定位技术的本质是一个优化最优问题;其次,在该基础上,以遗传算法、模拟退火算法、进化策略和差分进化算法作为研究对象,针对这4种典型定位算法的优缺点展开讨论;然后,结合GA算法和SA算法各自的优势,提出一种遗传-模拟退火算法,从而增加初始种群的多样性,避免在传感器节点选择中陷入局部最优解的问题;最后,将上述改进方法应用到无线传感器网络节点定位中,用MATLAB分别对GA算法、SA算法和GSA算法进行仿真比较,验证了GSA算法的优势,为无线传感节点自定位技术提供新的参考。

关键词: 无线传感器,网络节点,自定位算法,遗传-模拟退火算法

Abstract: This paper firstly summarized and analyzed basic principle and classification of the wireless sensor network node,and got that essence of self localization technology is an optimal problem.Secondly,on this basis,we took the genetic algorithm,simulated annealing algorithm,evolutionary strategy and differential evolution algorithm as the research object,and discussed the advantages and disadvantages of the four kinds of typical localization algorithm.Then,combined with the advantages of GA algorithm and SA algorithm respectively,a genetic simulated annealing algorithm was proposed,thereby improving the initial population diversity and avoiding the local optimal solution problem in sensor node selection.Finally the improved method was applied to locate wireless sensor network node,with Matlab respectively on the GA algorithm,SA algorithm and GSA algorithm simulation,and the advantages of GSA algorithm were verified for free wire sensing node self localization technology to provide a new reference.

Key words: Wireless sensor,Network node,Self localization algorithm,Genetic simulated annealing algorithm

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