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An Adaptive QoE-Based Network Interface Selection for Multi-homed eHealth Devices

  • Sami SouihiEmail author
  • Mohamed Souidi
  • Abdelhamid Mellouk
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 169)

Abstract

Conventional network control mechanisms are no longer suitable for Internet of Things (IoT) because they don’t allow scalability with a guarantee of Quality of Experience (QoE) especially when it comes to the health sector characterized by its real time and critical life aspects. That’s why we need to think differently about control. One aspect consists of improving the network accessibility by considering Multi-homed terminals using multiple network access points simultaneously. In this paper we present a new Q-Learning-based adaptive network interface selection approach. Experimental results show that the proposed approach involve QoE compared to a simple linear programming approach. abstract environment.

Keywords

Reinforcement Learning Q-learning Quality of Experience Mean Opinion Score (MOS) Multi-homed devices ICT health Internet of Things (IoT) 

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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2016

Authors and Affiliations

  • Sami Souihi
    • 1
    Email author
  • Mohamed Souidi
    • 1
  • Abdelhamid Mellouk
    • 1
  1. 1.Image, Signal and Intelligent Systems Lab (LiSSi), Network and Telecoms Dept, IUT CVUniversity of Paris-Est Crteil Val de Marne (UPEC)Vitry sur SeineFrance

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