31,579 research outputs found
Reliable Video Streaming over mmWave with Multi Connectivity and Network Coding
The next generation of multimedia applications will require the
telecommunication networks to support a higher bitrate than today, in order to
deliver virtual reality and ultra-high quality video content to the users. Most
of the video content will be accessed from mobile devices, prompting the
provision of very high data rates by next generation (5G) cellular networks. A
possible enabler in this regard is communication at mmWave frequencies, given
the vast amount of available spectrum that can be allocated to mobile users;
however, the harsh propagation environment at such high frequencies makes it
hard to provide a reliable service. This paper presents a reliable video
streaming architecture for mmWave networks, based on multi connectivity and
network coding, and evaluates its performance using a novel combination of the
ns-3 mmWave module, real video traces and the network coding library Kodo. The
results show that it is indeed possible to reliably stream video over cellular
mmWave links, while the combination of multi connectivity and network coding
can support high video quality with low latency.Comment: To be presented at the 2018 IEEE International Conference on
Computing, Networking and Communications (ICNC), March 2018, Maui, Hawaii,
USA (invited paper). 6 pages, 4 figure
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
Adaptive Video Streaming with Network Coding enabled Named Data Networking
The fast and huge increase of Internet traffic motivates the development of new communication methods that can deal with the growing volume of data traffic. To this aim, named data networking (NDN) has been proposed as a future Internet architecture that enables ubiquitous in-network caching and naturally supports multipath data delivery. Particular attention has been given to using dynamic adaptive streaming over HTTP to enable video streaming in NDN as in both schemes data transmission is triggered and controlled by the clients. However, state-of-the-art works do not consider the multipath capabilities of NDN and the potential improvements that multipath communication brings, such as increased throughput and reliability, which are fundamental for video streaming systems. In this paper, we present a novel architecture for dynamic adaptive streaming over network coding enabled NDN. In comparison to previous works proposing dynamic adaptive streaming over NDN, our architecture exploits network coding to efficiently use the multiple paths connecting the clients to the sources. Moreover, our architecture enables efficient multisource video streaming and improves resiliency to Data packet losses. The experimental evaluation shows that our architecture leads to reduced data traffic load on the sources, increased cache-hit rate at the in-network caches and faster adaptation of the requested video quality by the clients. The performance gains are verified through simulations in a Netflix-like scenario
Collaborative video streaming with Raptor network coding
We investigate the problem of collaborative video streaming with Raptor network coding over overlay networks. We exploit path and source diversity, as well as basic processing capabilities of network nodes to increase the overall throughput and improve the video quality at the clients. We consider an architecture where several streaming servers simultaneously deliver video information to a set of clients. The servers apply Raptor coding on the video packets for error resiliency, and the forwarding peer nodes further combine the Raptor coded video packets in order to increase the packet diversity in the network. We find the optimal source and channel rate allocation in such a collaborative streaming system. The resulting scheme efficiently exploits the available network resources for improved video quality. The experimental evaluation demonstrates that it typically outperforms Raptor video streaming systems that do not use network coding
Avoiding Interruptions - QoE Trade-offs in Block-coded Streaming Media Applications
We take an analytical approach to study Quality of user Experience (QoE) for
video streaming applications. First, we show that random linear network coding
applied to blocks of video frames can significantly simplify the packet
requests at the network layer and save resources by avoiding duplicate packet
reception. Network coding allows us to model the receiver's buffer as a queue
with Poisson arrivals and deterministic departures. We consider the probability
of interruption in video playback as well as the number of initially buffered
packets (initial waiting time) as the QoE metrics. We characterize the optimal
trade-off between these metrics by providing upper and lower bounds on the
minimum initial buffer size, required to achieve certain level of interruption
probability for different regimes of the system parameters. Our bounds are
asymptotically tight as the file size goes to infinity.Comment: Submitted to ISIT 2010 - Full versio
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