Speeding up Future Video Distribution via Channel-Aware Caching-Aided Coded Multicast

Future Internet usage will be dominated by the consumption of a rich variety of online multimedia services accessed from an exponentially growing number of multimedia capable mobile devices. As such, future Internet designs will be challenged to provide solutions that can deliver bandwidth-intensive, delay-sensitive, on-demand video-based services over increasingly crowded, bandwidth-limited wireless access networks. One of the main reasons for the bandwidth stress facing wireless network operators is the difficulty to exploit the multicast nature of the wireless medium when wireless users or access points rarely experience the same channel conditions or access the same content at the same time. In this paper, we present and analyze a novel wireless video delivery paradigm based on the combined use of channel-aware caching and coded multicasting that allows simultaneously serving multiple cache-enabled receivers that may be requesting different content and experiencing different channel conditions. To this end, we reformulate the caching-aided coded multicast problem as a joint source-channel coding problem and design an achievable scheme that preserves the cache-enabled multiplicative throughput gains of the error-free scenario,by guaranteeing per-receiver rates unaffected by the presence of receivers with worse channel conditions.Comment: 11 pages,6 figures,to appear in IEEE JSAC Special Issue on Video Distribution over Future Interne

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

Minimizing the impact of delay on live SVC-based HTTP adaptive streaming services

HTTP Adaptive Streaming (HAS) is becoming the de-facto standard for Over-The-Top video streaming services. Video content is temporally split into segments which are offered at multiple qualities to the clients. These clients autonomously select the quality layer matching the current state of the network through a quality selection heuristic. Recently, academia and industry have begun evaluating the feasibility of adopting layered video coding for HAS. Instead of downloading one file for a certain quality level, scalable video streaming requires downloading several interdependent layers to obtain the same quality. This implies that the base layer is always downloaded and is available for playout, even when throughput fluctuates and enhancement layers can not be downloaded in time. This layered video approach can help in providing better service quality assurance for video streaming. However, adopting scalable video coding for HAS also leads to other issues, since requesting multiple files over HTTP leads to an increased impact of the end-to-end delay and thus on the service provided to the client. This is even worse in a Live TV scenario where the drift on the live signal should be minimized, requiring smaller segment and buffer sizes. In this paper, we characterize the impact of delay on several measurement-based heuristics. Furthermore, we propose several ways to overcome the end-to-end delay issues, such as parallel and pipelined downloading of segment layers, to provide a higher quality for the video service