A Quality of Experience Management Framework for Mobile Users

Voice transmission is no longer the main usage of mobile phones. Data transmissions, in particular Internet access, are very common actions that we might perform with these devices. However, the spectacular growth of the mobile data demand in 5G mobile communication systems leads to a reduction of the resources assigned to each device. Therefore, to avoid situations in which the Quality of Experience (QoE) would be negatively affected, an automated system for degradation detection of video streaming is proposed. This approach is named QoE Management for Mobile Users (QoEMU). QoEMU is composed of several modules to perform a real-time analysis of the network traffic, select a mitigation action according to the information of the traffic and to some predefined policies, and apply these actions. In order to perform such tasks, the best Key Performance Indicators (KPIs) for a given set of video traces are selected. A QoE Model is trained to define a global QoE for the set of traces. When an alert regarding degradation in the quality appears, a proper mitigation plan is activated to mitigate this situation. The performance of QoEMU has been evaluated over a degradation situation experiments with different video users.

Social-Aware Cooperative Video Distribution via SVC Streaming Multicast

Scalable Video Coding (SVC) streaming multicast is considered as a promising solution to cope with video traffic overload and multicast channel differences. To solve the challenge of delivering high-definition SVC streaming over burst-loss prone channels, we propose a social-aware cooperative SVC streaming multicast scheme. The proposed scheme is the first attempt to enable D2D cooperation for SVC streaming multicast to conquer the burst-loss, and one salient feature of it is that it takes fully into account the hierarchical encoding structure of SVC in scheduling cooperation. By using our scheme, users form groups to share video packets among each other to restore incomplete enhancement layers. Specifically, a cooperative group formation method is designed to stimulate effective cooperation, based on coalitional game theory; and an optimal D2D links scheduling scheme is devised to maximize the total decoded enhancement layers, based on potential game theory. Extensive simulations using real video traces corroborate that the proposed scheme leads to a significant gain on the received video quality.

Observing to Understand, Understanding to Develop

Observing teaching-learning situations in order to better understand them, such was the OPEN project (Altet, Bru and Blanchard-Laville, 2012). This project has been transformed into the research federative structure of OPÉEN&ReForm (the passage from observation by research to observation for training being at stake). In this chapter, the resort to the video aiming at analyzing the activity is carried out according to an approach of professional didactics (Pastré, 2011; Vinatier, 2013) with the purpose to help the professionals in their development (Vinatier, 2013). The authors introduce the case study of a co-analysis approach of the video traces of a teacher activity, according to her point of view, in a collaborative research (Vinatier et al., 2012) in French Polynesia, what seems to constitute for her a potential situation of professional development (Mayen, 1999), in her authorizing herself to try out new ways to lead her teaching.