Bsoft (Italy)

Dynamic Adaptive Streaming over HTTP (DASH) is referred to as a multimedia streaming standard to deliver high quality multimedia content over the Internet using conventional HTTP Web servers. As a fundamental feature, it enables automatic switching of quality levels according to network conditions, user requirements, and expectations. Currently, the proposed adaptation schemes for HTTP streaming mostly rely on throughput measurements and/or buffer-related metrics, such as buffer exhaustion and levels. In this paper, we propose to enhance the DASH adaptation logic by feeding it with additional information from our evaluation of the users' perception approximating the user-perceived quality of video playback. The proposed model aims at conveniently combining TCP-, buffer-, and media content-related metrics as well as user requirements and expectations to be used as an input for the DASH adaptation logic. Experiments have demonstrated that the chosen model enhances the capability of the adaptation logic to select the optimal video quality level. Finally, we integrated all our findings into a real DASH system with QoE monitoring capabilities.

Increasingly popular multimedia services are expected to play a dominant role in the future of the Internet. In this context, it is essential that content-aware networking (CAN) architectures explicitly address the efficient delivery and processing of multimedia content. This article proposes the adoption of a content-aware approach into the network infrastructure, thus making it capable of identifying, processing, and manipulating media streams and objects in real time to maximize quality of service (QoS) and experience (QoE). Our proposal is built on the exploitation of scalable media coding technologies within such a content-aware networking environment. This discussion is based on four representative use cases for media delivery (unicast, multicast, peer-to-peer, and adaptive HTTP streaming) and reviews CAN challenges, specifically flow processing, caching/buffering, and QoS/QoE management.