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文章基本信息

  • 标题:Efficient Prediction of Network Traffic for Real-Time Applications
  • 作者:Muhammad Faisal Iqbal ; Muhammad Faisal Iqbal ; Muhammad Zahid
  • 期刊名称:Journal of Computer Networks and Communications
  • 印刷版ISSN:2090-7141
  • 电子版ISSN:2090-715X
  • 出版年度:2019
  • 卷号:2019
  • DOI:10.1155/2019/4067135
  • 出版社:Hindawi Publishing Corporation
  • 摘要:Accurate real-time traffic prediction is required in many networking applications like dynamic resource allocation and power management. This paper explores a number of predictors and searches for a predictor which has high accuracy and low computation complexity and power consumption. Many predictors from three different classes, including classic time series, artificial neural networks, and wavelet transform-based predictors, are compared. These predictors are evaluated using real network traces. Comparison of accuracy and cost, both in terms of computation complexity and power consumption, is presented. It is observed that a double exponential smoothing predictor provides a reasonable tradeoff between performance and cost overhead.
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