03 Dec QUEST
Quality of Experience of video streaming in wireless networks
StreamOwl was selected at the First Open call of WiSHFUL to conduct an experiment which employs advanced solutions for controlling wireless networks using the WiSHFUL software platforms and unified programming interfaces (UPIs), and using the facilities and hardware supported by the WiSHFUL Consortium.
The WiSHFUL project focuses on speeding up the development and testing cycles of wireless solution developments. It defines software modules with unified interfaces that permit wireless developers to quickly implement and validate advanced wireless network solutions. The software modules will enable the quick and efficient tuning of radio and/or network parameters to find the best configuration given the wireless device’s operating environment. The software modules will also be reprogrammable with other, new modules, which can be downloaded from app-store like repositories.
The QUEST project aims at developing an experiment based on the WiSHFUL testbed to highlight the QoE improvements by a cross-layer end-to-end approach for video streaming. At the network layer, Software Defined Networking (SDN) enables the virtualization of the network functions so that the network operators implement their own rules and policies in software and deploy them in an abstracted and virtualized network infrastructure. At the application layer, the Dynamic Adaptive Streaming over HTTP (DASH) approach enables the seamless adaptation of the video client to the specific network conditions of each user. The understanding of the impact of the network parameters and the media content on the human perception are key factors in optimizing the functions in the end-to-end delivery chain. The QUEST project will propose new network virtualisation functionalities, which takes into account the service utility functions, network topology, link capacities and the specific QoE requirements of each application. The experiment will be deployed based on the testbed from w.iLab.t of iMinds by exploiting the existing equipment (e.g. wireless cards, sensor nodes, Unified Programming Interfaces, etc.) and it will enable the benchmarking with traditional technologies and the quantification of improvements in terms of perceived quality, as defined by objective metrics and subjective tests.