Random Linear Network Coding for 5G Mobile Video Delivery

An exponential increase in mobile video delivery will continue with the demand for higher resolution, multi-view and large-scale multicast video services. Novel fifth generation (5G) 3GPP New Radio (NR) standard will bring a number of new opportunities for optimizing video delivery across both 5G core and radio access networks. One of the promising approaches for video quality adaptation, throughput enhancement and erasure protection is the use of packet-level random linear network coding (RLNC). In this review paper, we discuss the integration of RLNC into the 5G NR standard, building upon the ideas and opportunities identified in 4G LTE. We explicitly identify and discuss in detail novel 5G NR features that provide support for RLNC-based video delivery in 5G, thus pointing out to the promising avenues for future research.Comment: Invited paper for Special Issue "Network and Rateless Coding for Video Streaming" - MDPI Informatio

Robust multi-view video streaming through adaptive intra refresh video transcoding

A multi-view video (MVV) transcoder has been designed. The objective is to deliver maximum quality 3D video data from the source to the 2D video destination, through a wireless communication channel using all of its available bandwidth. This design makes use of the spatial and view downscaling algorithm. The method involves the reuse of motion information obtained from both the reference frames and views. Consequently, highly compressed MVV is converted into low bit rate single view video that is compliant with H.264/AVC format. Adaptive intra refresh (AIR) error resilience tool is configured to mitigate the error propagation resulting from channel conditions. Experimental results indicate that error resilience plus transcoding performed better than the cascaded technique. Simulation results demonstrated an efficient 3D video streaming service applied to low power mobile devices

Editorial -Special issue on adaptive multimedia computing

In recent years, there is an emerging research area in multimedia computing, with the increasing number of related work in scalable video, adaptive multimedia documents, adaptive multimedia services, to name just a few. This new trend comes about partly due to the increasing use of mobile media devices where media requirements could change among users and devices and at different times of reception or presentation, and partly due to the changing network conditions, where best-effort service is the general practice. Any change in Quality of Services (QoS) could imply a change in the delivery or scheduling of media contents. To complicate the matter, user interruptions or requirement changes during the communication process could also occur; for example, a user may not be satisfied with the current media quality and decide an upgrade in real time. The status quo is that this new research paradigm is beginning to take shape while no effort has been made to draw a roadmap for it. We could see some major research work missing, for example, formal methods or modeling of adaptive multimedi

Study of a Framework For Video Streaming In Mobile Devices (AMoV and ESoV)

AMoV (adaptive mobile video streaming) and ESoV(efficient social video sharing) are the terms which are currently gaining the attention of variety of computer users and researchers. While enjoying the multimedia services like videos and images, the basic quandary faced by any individual is the progressive downloading or the buffering of the videos. As the researches are focusing on various technologies in said issue, very least focus is given on to the security issues present in these technologies. The basic idea behind this paper is to study and to survey the literature and to propose the security aspects in related field

Quality of experience-centric management of adaptive video streaming services : status and challenges

Video streaming applications currently dominate Internet traffic. Particularly, HTTP Adaptive Streaming ( HAS) has emerged as the dominant standard for streaming videos over the best-effort Internet, thanks to its capability of matching the video quality to the available network resources. In HAS, the video client is equipped with a heuristic that dynamically decides the most suitable quality to stream the content, based on information such as the perceived network bandwidth or the video player buffer status. The goal of this heuristic is to optimize the quality as perceived by the user, the so-called Quality of Experience (QoE). Despite the many advantages brought by the adaptive streaming principle, optimizing users' QoE is far from trivial. Current heuristics are still suboptimal when sudden bandwidth drops occur, especially in wireless environments, thus leading to freezes in the video playout, the main factor influencing users' QoE. This issue is aggravated in case of live events, where the player buffer has to be kept as small as possible in order to reduce the playout delay between the user and the live signal. In light of the above, in recent years, several works have been proposed with the aim of extending the classical purely client-based structure of adaptive video streaming, in order to fully optimize users' QoE. In this article, a survey is presented of research works on this topic together with a classification based on where the optimization takes place. This classification goes beyond client-based heuristics to investigate the usage of server-and network-assisted architectures and of new application and transport layer protocols. In addition, we outline the major challenges currently arising in the field of multimedia delivery, which are going to be of extreme relevance in future years