通信工程

传感器网络微分环节中改进的最佳二阶近似模流量控制

展开
  • 重庆大学自动化学院, 重庆400030
倪晓,副教授,研究方向:嵌入式系统,E-mail: nixiao@hotmail.com;石为人,教授,博导,研究方向:智能感知、控制与决策、嵌入式系统等,E-mail:wrs@cqu.edu.cn

收稿日期: 2011-09-06

  修回日期: 2011-09-29

  网络出版日期: 2012-09-25

Flow Control of Optimum Second Order Approximation Modulus with Improved Differentiation Element in Sensor Networks

Expand
  • College of Automation, Chongqing University, Chongqing 400030, China

Received date: 2011-09-06

  Revised date: 2011-09-29

  Online published: 2012-09-25

摘要

自组织无线传感器网络的结构组合具有随机性,当节点传输数据时,数据缓冲区很容易发生传输拥塞.为解决这个问题,该文提出对微分环节进行改进的最佳二阶近似模流量控制方法. 该方法把传感器网络设计抽象成一个控制器,此控制器具有最佳二阶近似模传递函数. 控制器把节点数据缓冲区的实际数据高度负反馈到输入端,根据缓冲区实际高度和理想高度的差值大小,由控制器控制上游节点发送数据的速率. 为了减小系统超调量和使峰值提前,在传递函数中再加入一个微分环节,以确保网络在暂态和稳态阶段缓冲区数据都不会发生溢出.

本文引用格式

倪晓, 石为人, 黄勤 . 传感器网络微分环节中改进的最佳二阶近似模流量控制[J]. 应用科学学报, 2012 , 30(5) : 473 -478 . DOI: 10.3969/j.issn.0255-8297.2012.05.006

Abstract

Because self-organized wireless sensor network is randomly setup, data transmission among the nodes is subject to traffic jam. To address this problem, this paper proposes a method of optimum second order approximation modulus with an improved differentiation element to control data transmission. The controller applies a function of the optimum second order approximation modulus as its transfer function. It negatively
feedbacks the data buffer length in a node to its input point, and controls the speed of data transmission of the up-stream node. A differential element is added to the transfer function to reduce over-modulation and speed the peak emergence. Thus no traffic overflow will occur both in transition and in permanent periods.

参考文献

[1] Zhang X, Wicker S B. How to distribute sensors in a random field [C]//Proceeding of Third International Symposium on Information Processing in
Sensor Networks (IPSN), Berkeley, California, USA,2004.
[2] Xie Lei, Chen Lijun. Clustering-based approximate scheme for data aggregation over sensor networks [J].Journal of Software, 2009, 20(4): 1023-1037.
[3] Heinzelman W, Chandrakasan A. Energy efficient communication protocol for wireless micro sensor networks [C]//Proceeding of the 33rd Annual Hawaii International Conference on System Sciences, 2000:3005-3014.
[4] Wu Xuechun, Feng Bin. Recursion level of flow control mechanism in wireless sensor networks [J]. Computer Engineering and Applications, 2009, 45(4):119-121.
[5] Shen Wei, Hu Lishen. The design of traffic control system in networks-Kalman control algorithm [J]. Journal of China Institute of Communication, 2003,24(4): 48-56.
[6] Kim A N, Ramstad T A. Bandwidth expansion in a simple Gaussian sensor network using feedback [C]//Proceeding of 2010 Data Compression Conference (DDC), 2010: 259-268.
[7] Talukder A, Panangadan A, Herrington A T. Autonomous adaptive resource management in sensor network systems for environmental monitoring
[C]//Proceeding of IEEE Aerospace Conference,2008: 1-9.
[8] Gastpar M. On capacity under receive and spatial spectrum-sharing constraints [C]//IEEE Transactions on Information Theory, 2007, 53(2): 471-487.
[9] Zhang Jingyi, Ma Yongxuan. Study on system compensation control with pure time delay aspects and difference implementation [J]. Journal of Shenyang Normal University: Natural Science, 2010, 27(3): 310-313.
[10] De Arruda G H M. Relay based closed loop transfer function estimation [C]//Proceedings of the American Control Conference, 2000: 1812-1816.
[11] Samassi L, Tahraoui R. How to state necessary optimality conditions for control problems with deviating arguments [J]. Comptes Rendus Mathematique, 2004, 338(8): 611-616.

文章导航

/