SDN-based Wi-Fi Direct Clustering for Cloud Access in Campus Networks

Abstract : Mobile cloud is changing the way to enroll teaching activities in university campus. Lectures and lab sessions can be carried out directly from tablets in a class room by accessing a server in the cloud. In this paper, we address the problem of high density cloud access with wireless devices in campus networks. We propose to use Wi-Fi Direct clustering to solve the problem of Quality of Service (QoS) degradation when a high number of wireless devices want to access a content in the cloud at the same time. A centralized software-defined network controller is used in our proposed architecture to capture the network state and organize the Wi-Fi Direct groups. The optimized number of clusters can be calculated in function of the number of devices in the room. By simulations, we show that we can provide a better QoS in terms of download time and application's throughput by reducing the interference in this dense wireless network environment.
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Article dans une revue
Annals of Telecommunications, Springer, 2017, 〈10.1007/s12243-017-0598-z〉
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http://hal.upmc.fr/hal-01567735
Contributeur : Thi-Mai-Trang Nguyen <>
Soumis le : lundi 24 juillet 2017 - 13:39:37
Dernière modification le : jeudi 11 janvier 2018 - 06:28:03

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Thi-Mai-Trang Nguyen, Lyes Hamidouche, Fabien Mathieu, Sébastien Monnet, Syphax Iskounen. SDN-based Wi-Fi Direct Clustering for Cloud Access in Campus Networks. Annals of Telecommunications, Springer, 2017, 〈10.1007/s12243-017-0598-z〉. 〈hal-01567735〉

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