计算机工程 ›› 2020, Vol. 46 ›› Issue (11): 238-245.doi: 10.19678/j.issn.1000-3428.0055963

• 移动互联与通信技术 • 上一篇    下一篇

基于布谷鸟搜索的模糊PID拥塞控制方法

石优, 林琳, 吴岩   

  1. 江苏大学 计算机科学与通信工程学院, 江苏 镇江 212013
  • 收稿日期:2019-09-10 修回日期:2019-11-27 发布日期:2019-12-03
  • 作者简介:石优(1995-),男,硕士研究生,主研方向为无线传感器网络、网络拥塞控制;林琳、吴岩,副教授。
  • 基金项目:
    江苏省高等学校自然科学研究重大项目(17KJA413001);江苏省工业网络安全技术重点实验室开放基金(STICB201905)。

Fuzzy PID Congestion Control Method Based on Cuckoo Search

SHI You, LIN Lin, WU Yan   

  1. School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013, China
  • Received:2019-09-10 Revised:2019-11-27 Published:2019-12-03

摘要: 无线传感器网络内多个移动节点在采集、接收和发送数据时,数据来源的不规律性会造成节点瞬间接收大量数据,从而引发严重的网络拥塞,然而现有网络拥塞控制方法计算精度较低。针对该问题,建立一种基于布谷鸟搜索算法的模糊比例-积分-微分(PID)拥塞控制模型(CFPID)。将PID控制器引入无线传感网络,采用模糊控制算法整定优化PID参数以提高计算精度,并利用布谷鸟搜索算法对模糊PID控制的量化因子和参数增量进行搜索优化,以实现对节点内消息队列长度的精准调控。实验结果表明,与PID、IBLUE等传统控制方法相比,本文方法对队列长度和丢包率的控制能力更强,网络吞吐量提高4%~8%。

关键词: PID控制, 模糊控制, 布谷鸟搜索算法, 网络拥塞, 无线传感器网络

Abstract: When multiple mobile nodes in Wireless Sensor Networks(WSNs)collect,receive and send data,the irregularity of data sources will cause nodes to receive a large amount of data instantaneously,resulting in serious network congestion.However,the existing network congestion control methods have low calculation accuracy.To solve the problem,this paper proposes a fuzzy Proportional-Integral-Differential(PID) congestion control model,CFPID,based on the Cuckoo Search(CS) algorithm.The PID controller is introduced into WSNs.Then the fuzzy control algorithm is used to adjust and optimize PID parameters to improve calculation accuracy,and the CS algorithm is used to search and optimize the quantization factor and parameter increment of fuzzy PID control,so as to realize the precise control of message queue length in nodes.Experimental results show that compared with the traditional control methods such as PID and IBLUE,the proposed method has stronger control ability on queue length and packet loss rate,and the network throughput is increased by 4%~8%.

Key words: PID control, fuzzy control, Cuckoo Search(CS) algorithm, network congestion, Wireless Sensor Networks(WSNs)

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