计算机应用 ›› 2017, Vol. 37 ›› Issue (9): 2470-2473.DOI: 10.11772/j.issn.1001-9081.2017.09.2470

• 网络与通信 • 上一篇    下一篇

基于自适应模糊控制器的无线传感器网络功率控制

胡黄水1, 沈玮娜1, 王出航2, 张邦成1   

  1. 1. 长春工业大学 计算机科学与工程学院, 长春 130012;
    2. 长春师范大学 计算机科学与技术学院, 长春 130026
  • 收稿日期:2017-03-08 修回日期:2017-04-23 出版日期:2017-09-10 发布日期:2017-09-13
  • 通讯作者: 王出航,wangchuhang@cncnc.edu.cn
  • 作者简介:胡黄水(1974-),男,湖南隆回人,副教授,博士,主要研究方向:无线传感器网络、轨道车辆动力学;沈玮娜(1993-),女,江苏无锡人,硕士研究生,主要研究方向:无线传感器网络;王出航(1976-),女,吉林长春人,副教授,硕士,主要研究方向:无线传感器网络、实时嵌入式系统;张邦成(1972-),男,吉林长春人,教授,博士,主要研究方向:机电检测与控制。
  • 基金资助:
    吉林省科技厅科技攻关计划项目(20140204037GX, 20150204073GX);吉林省发展与改革委员会经济结构战略调整引导专项基金资助项目(2014Y125);。

Self-adaptive fuzzy controller based power control for wireless sensor networks

HU Huangshui1, SHEN Weina1, WANG Chuhang2, ZHANG Bangcheng1   

  1. 1. College of Computer Science and Engineering, Changchun University of Technology, Changchun Jilin 130012, China;
    2. College of Computer Science and Technology, Changchun Normal University, Changchun Jilin 130026, China
  • Received:2017-03-08 Revised:2017-04-23 Online:2017-09-10 Published:2017-09-13
  • Supported by:
    This work is partially supported by Jilin Provincial Department of Science and Technology Research Project (20140204037GX, 20150204073GX), Jilin Province Development and Reform Commission Strategic Adjustment of Economic Structure to Guide the Special Fund (2014Y125).

摘要: 针对现有的无线传感器网络(WSN)功率控制方法存在的节点早死问题,提出一种考虑节点剩余能量的功率控制方法——SAFPC。首先,设计了具有"输入-输出-反馈"机制的两级模糊控制器系统模型,主控制器负责节点发射功率调节,从控制器负责期望节点度调节,自适应地根据网络中节点剩余能量来调节发射功率;然后,分别对主、从控制器的模糊化、模糊规则及解模糊过程进行了详细描述;最后,从网络收敛时间、平均能耗以及生命周期方面对SAFPC进行了仿真分析。实验结果表明,与模糊控制传输功率方法(FCTP)相比,SAFPC收敛速率快12.5%,在不同网络规模情况下节点平均能耗降低3.68%,网络生命周期延长7.9%。可见,SAFPC能有效延长网络生命周期,提高网络动态适应性及链路鲁棒性。

关键词: 无线传感器网络, 功率控制, 模糊控制器, 能耗均衡, 自适应性

Abstract: To solve the problem of node's premature death in existing power control methods for Wireless Sensor Network (WSN), a new method called Self-Adaptive Fuzzy Control (SAFPC) was proposed. Firstly, the model of two level fuzzy controller with "input-output-feedback" mechanism was designed, whose main controller was responsible for the node transmission power adjustment, and auxiliary controller was responsible for the desired node degree adjustment, so as to adjust the transmission power adaptively according to the residual energy of the node. Secondly, the fuzzification, fuzzy rules and defuzzification process were described in detail. Finally, SAFPC was simulated and analyzed in terms of network convergence time, average energy consumption and network life cycle. The experimental results show that, compared with FCTP (Fuzzy Control Transmission Power method), SAFPC can increase convergence rate by 12.5%, the average energy consumption of the nodes is reduced by 3.68% and the network life cycle is prolonged by 7.9%. It can be seen that SAFPC can effectively prolong the network life cycle, as well as improve network dynamic adaptability and link robustness significantly.

Key words: Wireless Sensor Network (WSN), power control, fuzzy logic controller, balanced-energy consumption, adaptivity

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