June 23, 2013
June 23, 2013
June 26, 2013
Computing & Information Technology
23.420.1 - 23.420.6
Development of a Multi‐Platform High Performance Computing Streaming Video Distribution Cluster Abstract The _______________ developed a multiplatform (PC, iPhone, Android) streaming video platform to distribute distance‐learning content using a variety of HPC techniques. The developed system is capable of dynamically scaling and transcoding content based on server demand, available bandwidth, format of source material, and client format restrictions. The ______ needed a mechanism for distributing distance‐learning content to off‐site students. The group evaluated a wide range of commercial and open‐source streaming platforms using a robust set of objective criteria. The most important criteria were identified as: (1) ability to stream content to any common client (PCs/Macs, Tablets, mobile phones), (2) ability to encode / transcode content into any necessary format in real‐time or faster, (3) ability to adequately handle adverse conditions such as network congestion, and (4) ability to handle a large number of simultaneous client requests. To accomplish encoding, the team erected a computing farm with a cluster of nodes dedicated to real‐time video encoding. At the core of the encoding process were dedicated hardware h.264 encoders that accepted our videos as 1080p via HDMI and/or SDI and output h.264 files ranging in data‐rate from 2 to 20 Mbps. Lower bitrate files were created with off‐the‐shelf encoding software capable of utilizing NVidia Quadro and Tesla GPUs on the servers. A customized deployment of Wowza and JWplayer running on multiple servers stream content to the clients via HTTP pseudostreaming or RTMP based on the clients’ requirements. JWplayer identifies the client and routes calls to the appropriate streaming points on the Wowza server. Wowza gauges stream requirements and serves the content appropriately. In the end, the created solution meets all of the project’s goals of delivering any of the videos to any of the common platforms in a very robust and scalable manner.
Morales, C. R., & Cox, P. L., & Farrenkopf, M. J., & Knorr, R. E., & Morales, E., & Gaeta, C., & Durchholz, M. J. (2013, June), Development of a Multi-Platform High Performance Computing Streaming Video Distribution Cluster Paper presented at 2013 ASEE Annual Conference & Exposition, Atlanta, Georgia. https://peer.asee.org/19434
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