Scalable QoE-aware Path Selection In SDN-based Mobile Networks

Roberto Iraja Tavares Da Costa Filho Federal University of Rio Grande do Sul, Brazil
William R Lautenschlager Federal University of Rio Grande do Sul, Brazil
Nicolas Kagami Federal University of Rio Grande do Sul, Brazil
Marcelo Caggiani Luizelli Federal University of Pampa, Brazil
Valter Roesler Federal University of Rio Grande do Sul (UFRGS), Brazil
Luciano Paschoal Gaspary Federal University of Rio Grande do Sul, Brazil


To deal with the massive traffic produced by video applications, mobile operators rely on offloading technologies such as Small Cells, Content Delivery Networks and, shortly, Cloud Edge and 5G Device to Device communications. Although these techniques are fundamental for improving network efficiency , they produce a multitude of paths onto which the user traffic can be forwarded. Thus, a critical problem arises about how to handle the increasing video traffic while managing the interplay between infrastructure optimization and the user's Quality of Experience (QoE). Solving this problem is remarkably difficult, and recent investigations do not consider the large-scale context of mobile operator networks. To address this issue, we present a novel QoE-aware path deployment scheme for large-scale SDN-based mobile networks. The scheme relies on both a polynomial-time algorithm for composing multiple QoS metrics and a scalable QoS to QoE translation strategy. Considering real mobile operator network and video traffic traces, we show that the proposed algorithm outperformed state-of-the-art approaches by reducing impaired videos in aggregate MOS by at least 37% and lowering accumulated video stall length four times.

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