Petru Nicolaescu

Petru is PhD candidate and research assistant in the Advanced Community Information Systems (ACIS) group at the Chair of Computer Science 5 (Databases & Information Systems) at RWTH Aachen University in Germany. He worked as project researcher in Learning Layers.

Infrastructure - Cloud Video Transcoder

Purpose

ClViTra2.0 (c.f. D6.2 [1]) is an example of flexible cloud service, developed firstly for the Tethys infrastructure and evolved towards a las2peer microservice within the Layers Box.
Built as a RESTful service, ClViTra2.0 can be instantiated on multiple physical instances in order to scale transcoding tasks across multiple computers. Videos can then be transcoded on any of these installed instances, depending on the overall physical resources availability.

Description

Video transcoding needs to be performed in order to achieve interoperability and adaptation for different platforms, provide a seamless multimedia experience and make the videos accessible on mobile and desktop devices. ClViTra2.0 was developed as a cloud-based solution for transcoding video files and served to create a uniform encoding for videos used by tools such as Ach so! or SeViAnno. ClViTra2.0 is a REST-based cloud service developed to provide scalable transcoding of multiple videos simultaneously and video storage using the Tethys/Layers Box APIs. ClViTra2.0 serves as an abstraction layer for the Tethys cloud storage API. ClViTra2.0 is part of the integration guidelines and was developed as example for Layers Use-cases, tool support and OpenID Connect (OIDC) integration.

Use Cases and Tool Support

OIDC login
Authorization of service calls using OIDC
Scaling in the cloud using multiple instances, realized based on standard-based protocols and the master-slave paradigm
Usage of messaging protocols at different levels (between cloud instances, near real-time notifications to end-users)
Usage of RESTful APIs for storing the transcoded videos

Developers and Contributors

References

M. Derntl, M. Kravcik, R. Klamma, I. Koren, P. Nicolaescu, D. Renzel, A. Hannemann, M. Shahriari, J. Purma, M. Bachl, E. Bellamy, R. Elferink, V. Tomberg, D. Theiler, and P. Santos, “Customizable Architecture for Flexible Small-Scale Deployment,” Learning Layers Project, Deliverable D6.2, 2014.