Supporting media workflows on an advanced cloud object store platform

The media industry faces daily challenges storing, managing and facilitating collaboration for vast amounts of video, photos, text, audio, and social media. This, together with increasing quality factors like high frame rates and Ultra-High resolution, drives the need for more dependable storage and scalable computation. As a solution to tackle these challenges, we describe the Active Media Store (AMS), which extends OpenStack Swift with storlets and content-centric access. Computation units called "Storlets" run typical media workflow functions, such as transcoding, metadata extraction and quality checks, close to the stored data, thereby reducing data transfer bandwidth and latency typically associated with cloud storage. Powerful search capabilities over rich user-defined metadata enable content-centric access, the ability to find stored media objects based on their content and relationships. Media workflows are easily implemented and managed through the Media Bridge, middleware running over the AMS and adapting its low level APIs. We describe an example workflow for file staging over this infrastructure in order to illustrate its power.

[1]  David L. Giaretta,et al.  Preservation DataStores: Architecture for Preservation Aware Storage , 2007, 24th IEEE Conference on Mass Storage Systems and Technologies (MSST 2007).

[2]  Erik Elmroth,et al.  A Cloud Environment for Data-intensive Storage Services , 2011, 2011 IEEE Third International Conference on Cloud Computing Technology and Science.

[3]  Algorithms to measure audio programme loudness and true-peak audio level , 2011 .

[4]  Bing Li,et al.  Distributed metadata management scheme in cloud computing , 2011, 2011 6th International Conference on Pervasive Computing and Applications.

[5]  Albrecht Kurze,et al.  A scalable open source framework for live media production and distribution , 2011, 2011 14th ITG Conference on Electronic Media Technology.

[6]  Jian Zhang,et al.  COSBench: cloud object storage benchmark , 2013, ICPE '13.

[7]  Sujit Dey Mobile cloud applications: opportunities, challenges and directions , 2013, MobileCloud '13.

[8]  M. Montenovo From the cloud to TV production: a real world case study of an architecture and performance model , 2014 .

[9]  Lidong Chen,et al.  An approach for fast and parallel video processing on Apache Hadoop clusters , 2014, 2014 IEEE International Conference on Multimedia and Expo (ICME).