Adaptive Video Streaming with Network Coding Enabled Named Data Networking

Saltarin de Arco, Jonnahtan Eduardo; Bourtsoulatze, Eirina; Thomos, Nikolaos; Braun, Torsten (2017). Adaptive Video Streaming with Network Coding Enabled Named Data Networking. IEEE transactions on multimedia, 19(10), pp. 2182-2196. IEEE 10.1109/TMM.2017.2737950

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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 multi-path data delivery. Particular attention has been given to using Dynamic Adaptive Streaming over HTTP (DASH) 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, that 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 multi-source 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.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 multi-source 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 innetwork caches and faster adaptation of the requested video quality by the clients. The performance gains are verified in a Netflix-like scenario.

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