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Mining and Control of Network Traffic by Computational Intelligence

  • Federico Montesino Pouzols
  • Diego R. Lopez
  • Angel Barriga Barros

Part of the Studies in Computational Intelligence book series (SCI, volume 342)

Table of contents

  1. Front Matter
  2. Federico Montesino Pouzols, Diego R. Lopez, Angel Barriga Barros
    Pages 1-51
  3. Federico Montesino Pouzols, Diego R. Lopez, Angel Barriga Barros
    Pages 53-85
  4. Federico Montesino Pouzols, Diego R. Lopez, Angel Barriga Barros
    Pages 87-145
  5. Federico Montesino Pouzols, Diego R. Lopez, Angel Barriga Barros
    Pages 147-189
  6. Federico Montesino Pouzols, Diego R. Lopez, Angel Barriga Barros
    Pages 191-262
  7. Federico Montesino Pouzols, Diego R. Lopez, Angel Barriga Barros
    Pages 263-304
  8. Back Matter

About this book

Introduction

As other complex systems in social and natural sciences as well as in
engineering, the Internet is hard to understand from a technical point
of view. Packet switched networks defy analytical modeling. The
Internet is an outstanding and challenging case because of its fast
development, unparalleled heterogeneity and the inherent lack of
measurement and monitoring mechanisms in its core conception.

This monograph deals with applications of computational intelligence
methods, with an emphasis on fuzzy techniques, to a number of current issues in measurement, analysis and control of traffic in the
Internet. First, the core building blocks of Internet Science and
other related networking aspects are introduced. Then, data mining and control problems are addressed. In the first class two issues are
considered: predictive modeling of traffic load as well as
summarization of traffic flow measurements. The second class, control, includes active queue management schemes for Internet routers as well as window based end-to-end rate and congestion control. The practical hardware implementation of some of the fuzzy inference systems proposed here is also addressed. While some theoretical developments are described, we favor extensive evaluation of models using real-world data by simulation and experiments.

Keywords

Computational Intelligence Fuzzy Inference Fuzzy Logic Network Traffic Soft Computing Time Series Prediction

Authors and affiliations

  • Federico Montesino Pouzols
    • 1
  • Diego R. Lopez
    • 2
  • Angel Barriga Barros
    • 3
  1. 1.Dept. of Information and Computer ScienceAalto University AaltoFinland
  2. 2.  RedIRIS, Red.es,Edif. Bronce MadridSpain
  3. 3. Instituto de Microelectrónica de Sevilla SevillaSpain

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-18084-2
  • Copyright Information Springer Berlin Heidelberg 2011
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-642-18083-5
  • Online ISBN 978-3-642-18084-2
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • Buy this book on publisher's site