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- A multi-layer probing approach for video over 5G in vehicular scenariosPublication . LOPES, RUI; Rocha, Filipe; Sargento, Susana; Luís, Miguel; Leitão, Ricardo; Marques, Eduardo; Antunes, BrunoFifth generation (5G) technologies are becoming a reality throughout the world. In parallel, vehicular networks rise their pace in terms of utilization; moreover, multimedia content transmissions are also getting an always increasing demand by their users. Besides the promised performance of 5G networks, several questions still arise among the community: are these networks capable of delivering high quality video streaming services in moving scenarios? What is the relationship between the network conditions and the video quality of experience? To answer to the previous questions, in this paper we propose a multi-layer probing approach able to assess video transmissions over 5G and 4G, combining data from all layers of a communication model, relating events from its origin layers. The probe's potential is thoroughly evaluated in two distinct video streaming use cases, both targeting a vehicular scenario supported by cellular 4G and 5G networks. Regarding the probe's performance, we show that a multitude of performance and quality indicators, from different stack layers, can be obtained. As for the performance of 4G and 5G networks in video streaming scenarios, the results have shown that the 5G links show a better overall performance in terms of video quality-of-experience, granting lower delays and jitter conditions, thus allowing video delay to be diminished and segment buffering to be better performed in comparison to 4G, while still showing adaptability in lightly traffic-saturated vehicular-to-vehicular scenarios.
- Real-time video frame differentiation in multihomed VANETsPublication . LOPES, RUI; Luís, Miguel; Sargento, SusanaProviding high quality video transmission in VANETs is very challenging due to the highly dynamic, unpredictable topology, and low bandwidth characteristics. In this article, we design a system able to optimally transmit RTP video streams in an IP-based multihomed VANET. By splitting the video through its different frame types in the array of multihomed paths from the center node of the network to the clients, the system can then send critical frames, depending on the used coding standard, through a more reliable path, in order to improve the video performance even if the quality is degraded due to bad signal reception. Two different content-based multihomed video distribution schemes have been proposed: linear selection, where the system is able to select more reliable paths for higher prioritized segments; and adaptive selection, where the paths are sensed to assess their congestion level in a real-time approach. Through real deployment of these approaches in a real vehicular scenario, with mobility, handovers and multihoming, the proposed approaches achieved a strong decrease in the loss percentage, with a maximum of approximately 60.4%, greatly improving the video quality while on the move.