• DocumentCode
    2810627
  • Title

    Research on Network Traffic Forecasting Strategy Based on BP Neural Network

  • Author

    Li, Yuanyuan ; Zhang, Ming

  • Author_Institution
    Coll. of Electron. Eng., Huaihai Inst. of Technol., Lianyungang, China
  • fYear
    2009
  • fDate
    11-13 Dec. 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    One major problem in the management of the current large networks is the complexity and the enormous amount of operations required to satisfy user demands while using resources efficiently. In this study, we propose a network traffic forecasting strategy based on BP neural network (BP-NTF). First, we analyse the characteristics of network traffic and establish traffic forecasting methods based on BP neural network, then modeling and forecasting the time series of network traffic data; Second, we construct three module, namely, data collection, data processing and traffic forecasting; Last, we use the strong memory and the learning ability of BP neural network to short-term forecast the network traffic .This model can provide a basis for network monitoring and management and has high application value and very wide meaning.
  • Keywords
    backpropagation; computerised monitoring; neural nets; BP neural network; learning ability; network traffic forecasting strategy; traffic forecasting methods; Data processing; Demand forecasting; Memory management; Monitoring; Neural networks; Predictive models; Resource management; Telecommunication traffic; Time series analysis; Traffic control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-4507-3
  • Electronic_ISBN
    978-1-4244-4507-3
  • Type

    conf

  • DOI
    10.1109/CISE.2009.5362972
  • Filename
    5362972