Using Fuzzy Logic Control to Provide Intelligent Traffic Management Service for High-Speed Networks

被引:7
|
作者
Liu, Jungang [1 ]
Yang, Oliver W. W. [1 ]
机构
[1] Univ Ottawa, Sch Elect Engn & Comp Sci, Ottawa, ON K1N 6N5, Canada
关键词
Congestion control; fuzzy logic control; quality of service; max-min fairness; robustness; traffic management; CONGESTION CONTROL; SYSTEM;
D O I
10.1109/TNSM.2013.043013.120264
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In view of the fast-growing Internet traffic, this paper propose a distributed traffic management framework, in which routers are deployed with intelligent data rate controllers to tackle the traffic mass. Unlike other explicit traffic control protocols that have to estimate network parameters (e.g., link latency, bottleneck bandwidth, packet loss rate, or the number of flows) in order to compute the allowed source sending rate, our fuzzy-logic-based controller can measure the router queue size directly; hence it avoids various potential performance problems arising from parameter estimations while reducing much consumption of computation and memory resources in routers. As a network parameter, the queue size can be accurately monitored and used to proactively decide if action should be taken to regulate the source sending rate, thus increasing the resilience of the network to traffic congestion. The communication QoS (Quality of Service) is assured by the good performances of our scheme such as max-min fairness, low queueing delay and good robustness to network dynamics. Simulation results and comparisons have verified the effectiveness and showed that our new traffic management scheme can achieve better performances than the existing protocols that rely on the estimation of network parameters.
引用
收藏
页码:148 / 161
页数:14
相关论文
共 50 条
  • [1] Traffic control in high-speed ATM networks
    Zhou, PF
    Yang, OWW
    7TH INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATIONS AND NETWORKS - PROCEEDINGS, 1998, : 183 - 190
  • [2] An efficient fuzzy system for traffic management in high-speed packet-switched networks
    G. Ascia
    V. Catania
    D. Panno
    Soft Computing, 2001, 5 (4) : 247 - 256
  • [3] Fuzzy neural network based traffic prediction and congestion control in high-speed networks
    Xiang Fei
    Xiaoyan He
    Junzhou Luo
    Jieyi Wu
    Guanqun Gu
    Journal of Computer Science and Technology, 2000, 15 : 144 - 149
  • [4] Fuzzy neural network based traffic prediction and congestion control in high-speed networks
    Fei, X
    He, XY
    Luo, JZ
    Wu, JY
    Gu, GQ
    JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY, 2000, 15 (02) : 144 - 149
  • [5] High-speed control of IPMSM drives using improved fuzzy logic algorithms
    Uddin, M. Nasir
    Rahman, M. Azizur
    IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2007, 54 (01) : 190 - 199
  • [6] Traffic modeling, prediction, and congestion control for high-speed networks: A fuzzy AR approach
    Chen, BS
    Peng, SC
    Wang, KC
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2000, 8 (05) : 491 - 508
  • [7] Dynamic Traffic Management Services To Provide High Performance In IntelRate Controller Using Fuzzy Logic
    Vasuki, M.
    Balkis, N.
    Jayalakshmi, V.
    INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY, 2015, 15 (11): : 67 - 75
  • [8] Fuzzy Neural Network Based Traffic Prediction and Congestion Control in High-Speed Networks
    费翔
    何小燕
    罗军舟
    吴介一
    顾冠群
    Journal of Computer Science and Technology, 2000, (02) : 144 - 149
  • [9] Admission control of multi-class traffic with service priorities in high-speed networks
    V.G. Kulkarni
    N. Gautam
    Queueing Systems, 1997, 27 : 79 - 97
  • [10] Admission control of multi-class traffic with service priorities in high-speed networks
    Kulkarni, VG
    Gautam, N
    QUEUEING SYSTEMS, 1997, 27 (1-2) : 79 - 97