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A Wearable Machine Learning Solution for Internet Traffic Classification in Satellite Communications

  • Fannia PachecoEmail author
  • Ernesto Exposito
  • Mathieu Gineste
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11895)

Abstract

In this paper, we present an architectural framework to perform Internet traffic classification in Satellite Communications for QoS management. Such framework is based on Machine Learning techniques. We propose the elements that the framework should include, as well as an implementation proposal. We define and validate some of its elements by evaluating an Internet dataset generated on an emulated Satellite Architecture. We also outline some discussions and future works that should be addressed in order to have an accurate Internet classification system.

Keywords

Internet traffic classification Machine Learning Satellite Communications Deep packet inspection 

Notes

Acknowledgment

We want to thank the Centre National d’Études Spatiales (CNES), Toulouse, France for allowing us to use the SAT data, which is developed under the project R&T CNES: Application du Machine Learning au Satcom.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Fannia Pacheco
    • 1
    Email author
  • Ernesto Exposito
    • 1
  • Mathieu Gineste
    • 2
  1. 1.Univ Pau & Pays Adour, E2S UPPA, LIUPPA, EA3000AngletFrance
  2. 2.Business Line TelecommunicationR&D départment, Thales Alenia SpaceToulouseFrance

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