Research Article
An Adaptive QoE-Based Network Interface Selection for Multi-homed eHealth Devices
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@INPROCEEDINGS{10.1007/978-3-319-47063-4_45, author={Sami Souihi and Mohamed Souidi and Abdelhamid Mellouk}, title={An Adaptive QoE-Based Network Interface Selection for Multi-homed eHealth Devices}, proceedings={Internet of Things. IoT Infrastructures. Second International Summit, IoT 360° 2015, Rome, Italy, October 27-29, 2015. Revised Selected Papers, Part I}, proceedings_a={IOT360}, year={2017}, month={1}, keywords={Reinforcement Learning Q-learning Quality of Experience Mean Opinion Score (MOS) Multi-homed devices ICT health Internet of Things (IoT)}, doi={10.1007/978-3-319-47063-4_45} }- Sami Souihi
Mohamed Souidi
Abdelhamid Mellouk
Year: 2017
An Adaptive QoE-Based Network Interface Selection for Multi-homed eHealth Devices
IOT360
Springer
DOI: 10.1007/978-3-319-47063-4_45
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. environment.
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