Journal of Computer Applications ›› 2017, Vol. 37 ›› Issue (6): 1539-1544.DOI: 10.11772/j.issn.1001-9081.2017.06.1539

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Dynamic clustering target tracking based on energy optimization in wireless sensor networks

WEI Mingdong, HE Xiaomin, XU Liang   

  1. School of Automation, Guangdong University of Technology, Guangzhou Guangdong 510006, China
  • Received:2016-11-10 Revised:2017-02-14 Online:2017-06-10 Published:2017-06-14
  • Supported by:
    This work is partially supported by the National Natural Science Foundation of China (21376091), the Guangdong Provincial Science and Technology Plan Project (2015A030401089).


魏明东, 何小敏, 许亮   

  1. 广东工业大学 自动化学院, 广州 510006
  • 通讯作者: 许亮
  • 作者简介:魏明东(1991-)男,湖南永州人,硕士研究生,主要研究方向:无线传感器网络;何小敏(1961-),女,广东广州人,副教授,硕士,主要研究方向:机器视觉、无线传感器网络;许亮(1971-),男,甘肃白银人,高级工程师,博士,主要研究方向:机器视觉、机器学习、无线传感器网络。
  • 基金资助:

Abstract: Concerning the problem of high energy consumption caused by data collision and cluster selection process in dynamic clustering target tracking of Wireless Sensor Network (WSN), a dynamic clustering method based on energy optimization for WSN was proposed. Firstly, a time division election transmission model was proposed, which avoided data collision actively to reduce energy consumption of nodes in a dynamic cluster. Secondly, based on energy information and tracking quality, the energy-balanced farthest node scheduling strategy was proposed, which optimized custer head node scheduling. Finally, according to the weighted centroid localization algorithm, the target tracking task was completed. Under the environment of random deployment of nodes, the experimental results show that, the average tracking accuracy of the proposed method for non-linear moving objects was 0.65 m, which is equivalent to that of Dynamic Cluster Member Selection method for multi-target tracking (DCMS), and improved by 45.8% compared to Distributed Event Localization and Tracking Algorithm (DELTA). Compared with DCMS and DELTA, the proposed algorithm can effectively reduce energy consumption of the dynamic tracking clusters by 61.1% and prolong the network lifetime.

Key words: Wireless Sensor Network (WSN), target tracking, energy optimization, dynamic clustering, time division election transmission model

摘要: 针对无线传感器网络动态分簇目标跟踪中的数据碰撞与簇首选择过程导致能耗过高问题,提出一种基于能量优化的无线传感器网络动态分簇方法。首先,构建时分竞选传输模型,主动避免动态簇内数据碰撞,降低节点能耗;然后,基于能量信息与跟踪质量,提出能量均衡的最远节点调度策略,优化簇头节点调度;最后,根据加权质心定位算法,完成目标跟踪任务。实验结果表明:在节点随机部署的环境下,所提方法对于非线性运动目标的平均跟踪精度为0.65 m,与多目标跟踪动态簇员选择方法(DCMS)相当,比分布式事件定位动态分簇目标跟踪算法(DELTA)提高了45.8%;能量消耗方面,与DCMS和DELTA相比,所提方法的动态跟踪簇能量消耗有效降低了61.1%,延长了网络寿命。

关键词: 无线传感器网络, 目标跟踪, 能量优化, 动态分簇, 时分竞选传输模型

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