=Paper=
{{Paper
|id=None
|storemode=property
|title=Render on the cloud: Using Cinelerra on Virtualized Infrastructures
|pdfUrl=https://ceur-ws.org/Vol-945/paper6.pdf
|volume=Vol-945
|dblpUrl=https://dblp.org/rec/conf/ltec/ZablahGGP12
}}
==Render on the cloud: Using Cinelerra on Virtualized Infrastructures==
https://ceur-ws.org/Vol-945/paper6.pdf
1st International Workshop on Cloud Education Environments (WCLOUD 2012)
Render on the cloud: Using Cinelerra on virtualized infrastructures
I. Zablah A. Garcia-Loureiro, F. Gomez-Folgar and T.F. Pena
Sistema de Difusión de Radio y Televisión Centro de Investigación en Tecnoloxı́as da Información (CITIUS)
Universidad Nacional Autónoma de Honduras University of Santiago de Compostela
Tegucigalpa, Honduras Santiago de Compostela, Spain
mrzablah@unah.tv (antonio.garcia.loureiro, fernando.gomez.folgar, tf.pena)@usc.es
Abstract—Nowadays, the learning-teaching processes are The cloud technology can be defined as some kind of
being supported by the use of new technologies, including parallel and distributed system [4], conformed by a lot
email, chat, online conferencing, online activities and video- of interconnected Virtual Machines (VM), or guest sys-
conferencing. With the revolution of high definition television,
video producers require more efficiency in the production and tems, providing dynamically computational resources on
post-production tasks. There are several software available demand as a unified one. They are based on a Service
for this purpose including commercial solutions, often very Level Agreement (SLA) [5]. This technology is growing
expensive, and open-source ones, such as Cinelerra. very fast as well as the computer resources that support
This paper proposes a cloud infrastructure for using Ci- it, specially the Service Oriented Architecture (SOA) [6]
nelerra, a community developed version of non-linear video
editor, and how educational institutions can use this. The main and the virtualization technology [3], using both hardware
idea is to reuse its computational power for editing or creating and software resources. The virtualization technology is the
educational videos without the need of acquiring a dedicated cornerstone of the cloud, as well known as Infrastructure as
hardware infrastructure, employing non dedicated resources, a Service (IaaS) [7]. The cloud technology can be used with
such as the computer labs, or desktop computers to fix the different objectives. In our case we are interested to know
most common time consuming problem: the rendering. The
performance of the proposed infrastructure is also presented the advantages of use it on video rendering process using
in this paper. the Cinelerra [8] application on a virtualized environment
provided by a hypervisor layer.
Keywords-Cinelerra; rendering; cloud; broadcast;
This paper is organized as follows. The section II de-
scribes the implementation of the proposed infrastructure
I. I NTRODUCTION
used to install Cinelerra and how use it to improve the ren-
Recently, technologies [1] such as email, chat, online dering process. The section III describes two cases of study
conferencing, online activities and videoconferencing were for the proposed infrastructure. The Section IV includes
incorporated to support teaching and learning processes. the performance evaluation of the proposed infrastructure
Today we live the biggest revolution on computing, mul- performing several rendering tests. Finally, the conclusions
timedia and TV, since the invention of color broadcast of this paper are drawn in section V.
in the beginning of fifties decade [2]. Currently, teachers
and students can watch videos on a variety of mediums, II. P ROPOSED I MPLEMENTATION
from mobile phones, computers and high definitions screens. The proposed infrastructure for executing Cinelerra,
These changes goes on the hand with the evolution of the shown in Fig. 1, is composed by several types of compo-
information technology. They used the computing power of nents: physical compute nodes, a virtual master node, virtual
the new computers to create videos of superior quality and render nodes and a Network File System (NFS), shared by
complexity from a bunch of source feeds. the virtual cluster.
It is well-known rendering is a time consuming task. The physical compute nodes are an Intel Core I7-2820QM
Usually, the companies and training centers use expensive processor with a clock speed of 2.30 GHz and 8 GB of
resources to reduce the edition time necessary to prepare DDR3 RAM, with the VirtualBox [9] 4.1.14 hypervisor
the videos. In an educational environment, it could be better installed. This processor reports eight cores (with hyper-
to create high quality videos without the need of incurring threading enabled). The master and the render nodes are Vir-
in license cost and without acquiring expensive dedicated tualBox VMs with two cores per VM, with 1 GB of RAM,
hardware resources. This paper focus on how it is possible taking advantage of the hardware virtualization extensions.
to reuse the existing computer hardware of educational The virtual cluster infrastructure (virtual master and virtual
institutions, such as schools, colleges and faculties to create compute nodes) uses Ubuntu 12.04 LTS 64 bits as guest
educational videos, by implementing cloud and virtualiza- operating system, employing a Gigabit Ethernet interface.
tion technology [3]. The NFS stores input and output video resources.
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1st International Workshop on Cloud Education Environments (WCLOUD 2012)
Figure 2. Use of Cinelerra at UNAH TV station.
Figure 1. Schematic view of the implementation.
In the Editing & Production department, the editors,
III. C ASES OF S TUDY equipped with powerful workstations, access to the hierar-
chical Video Storage to take the required resources that will
Two cases of study were proposed as examples of use of be incorporated into the Cinelerra video project, including
the infrastructure described previously. The first one is the sounds, videos, images, and production scenarios. Once the
implementation of Cinelerra over the infrastructure avail- video is edited, is ready for starting the rendering stage
able at the National Autonomous University of Honduras employing the computational power available at the Cloud
(UNAH). The second one is using Cinelerra in a training infrastructure that is composed by non-dedicated hardware
center. resources. The rendering stage ends with the creation of a
A. Cinelerra in the public UNAH TV channel final version of the ready to air TV program. The results of
The infrastructure proposed previously can be imple- the rendering process are stored in the Video Storage, which
mented at UNAH in order to help the process of producing can be taken by the operators of the Play Out department
television content for broadcast on the public TV channel to be transmitted and make them available to final users.
owned by the university, reducing the required time to obtain Those contents can be also accessed by the academic staff
the final content for airing. This infrastructure takes advan- from the classroom using the existing university network, or
tage of the virtualization technology and the Infrastructure to the general public employing Internet streaming.
as a Service (IaaS) paradigm, allowing reusing the hardware
B. Cinelerra as a tool in educational environments
available at UNAH for multiple applications.
Fig. 2 shows the work-flow that must be follow with the This scenario proposed the use of Cinelerra as a tool in
main objective to incorporate the advantages of rendering educational environments employing a cloud composed by
on the cloud. As shown in the figure, at UNAH TV station non dedicated hardware resources. In this case, the cloud
all the video and TV production starts with the introduction is employed as a rendering queue where the projects will
of the media content into the broadcasting system through be processed like in a batch system to get the ready to air
a common point called Input Resources or Ingest. Here videos. This case of study is shown in Fig. 3. As we can see,
employing a serie of procedures, videos from a camera, students create non-linear edition projects using Cinelerra in
studio, satellite, DVD, tape, etc. are converted in computer their workstations. Source videos, transitions effects, and the
video files accompanied with a standardized metadata files additional necessary media compose those projects. When
that describes their content and properties. the edition process is finished, the project is stored in
As a result of the previous process, in first place, the video the Master Node. This element shares the media directory
files are stored in the Video Storage, that is composed by employing the Network File System (NFS) protocol and has
a group of NFS servers configured with redundant arrays also Cinelerra installed as a render queue that manages the
of disk drives. In second place, the metadata is stored in jobs pending of being rendered. These jobs are dispatched
a database server. The Video Storage can be organized in to the Virtual Render Nodes in which the ready to air video
hierarchical levels to distinguish videos of different origin, is created. The Virtual Render Nodes are Cinelerra enabled
source, resources, media support and the edited ready to air VMs that mount the NFS directories shared by the Master
videos. Node. The virtual Render Nodes can be executed in the
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1st International Workshop on Cloud Education Environments (WCLOUD 2012)
Figure 4. Performance with 40 seconds of video at 1080/60p.
employing two cores each one. The purpose of the tests is to
know how much time is needed in every configuration and
Figure 3. Use of Cinelerra by students with virtual render nodes located
how the render process could be beneficed or penalized.
on remote computers on other rooms. When several nodes are used, we set the option in
Cinelerra that allows to automatically dividing the job in
several parts. Cinelerra itself splits the jobs trying to give
computer laboratories of the educational institutions. The the same number of render parts to all machines (including
video created by the rendering process is finally stored in the master). In this way, the number of files generated scale
the NFS shared directory of the Master Node. Notice that with the number of nodes employed (from one when only
the student’s workstations, the Master Node and the Virtual the master rendering, two, four, six, eight up to sixteen). This
Render Nodes must be accessible and interconnected by a method avoids that some rendering nodes were unused.
communications network. For the first test, the video of 40 s at 1080/60p, we can
The main goal of this scenario is the possibility to reuse see the obtained results in Fig. 4. The master needed more
the idle computational power available in the computer labs time to finish than the other configurations, except when
elastically, as they are available, to reduce the necessary time we used the master with one node and sixteen output files
to get the rendering process finished. that required 287 s, the worst performance in this test. The
best time was obtained employing the master and two nodes
IV. P ERFORMANCE E VALUATION using eight files, requiring 125 s only. Employing the same
In this section we included the performance analysis combination with four files the time required was 134 s.
of Cinelerra over the proposed infrastructure, as described Using the master and one node, the best result was quite the
previously. same using two and four output files; this was 153 s, this is
Cinelerra was used for editing and rendering video on res- 28 s more than the best result of all the present test.
olutions of 720p and 1080i, with input/output streams used Our second test was a project with an output video of
for high definition (HD) television. As a common standard 1800 s (30 minutes) at a standard resolution of 720p. In this
for audio/video the codec MPEG4 [10] was employed. It has project we joined some feeds and added transitions between
been on video editing world from last years of 90s decade. every resource, applying basic effects. The rendering process
To evaluate if the proposed cloud infrastructure could took 6487 s for the master. This was the worst result on the
be considered as a good option for rendering, we prepare present project. After adding one node to help the master, the
some tests. The first one was an output video of 40 seconds efficiency was improved. The best result in this combination
length with 1080/60p resolution. The second one was a video was 3605 s, allowing Cinelerra dividing the output render
of 30 minutes at 720p. The third one was a video of 30 job in six files. After adding a second node, the shortest and
minutes at 720p, composed by thirty feeds of one minute best time was obtained employing eight output files that took
without transitions or effects. We run the render tests only 3072 s only. The results are depicted in Fig. 5. Because the
in the master with two cores, later with one and two nodes, previous video project are not homogeneous and contains
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1st International Workshop on Cloud Education Environments (WCLOUD 2012)
Figure 5. Performance with 30 minutes of video at 720p.
Figure 6. Performance with 30 minutes of video at 1080/60p. Shortest
bars, better performance.
several types of effects and transitions, which mainly differ
in complexity, we consider to be very interesting to know
how the infrastructure proposed would behave to complete we want to render very small videos, the computing capacity
a project in which resources were homogeneous, allowing available on workstation used by the students or editors will
the nodes performing similar computational tasks. The third be sufficient to successfully complete the jobs.
test, as shown in Fig. 6, was prepared employing 30 feeds It is important to mention that the proposed solution,
one minute of video at 1080i without employing transitions. based on cloud rendering, will be helpful in the process
In this case, the better time was obtained with the master of creating multimedia for the TV station of the National
and two nodes, employing sixteen output files that required Autonomous University of Honduras, Therefore, we can
1226 s The result is very similar employing eight files. The provide to end users, in a short period, large amount of
render using the master required 2614 s, the worst elapsed quality television videos and multimedia using the idle
time in the present measures. Working with the master and computing power available.
one node, the best time was 1477 s, using with sixteen files.
The most important aspect of improving the rendering
We got similar results when this configuration is used with
process is to have a greater chance to train better technical
eight output files as the difference was 24 s only.
experts and to create fastest multimedia content, therefore,
V. C ONCLUSION the students will have more computational resources to
The use of cloud technologies to create high quality develop their projects and ideas, but without incurring in
videos in an educational environment is feasible without the cost of acquiring a dedicated infrastructure.
the need of incurring in license cost and without the need
of acquire expensive dedicated hardware resources. This ACKNOWLEDGMENT
paper analysed a cloud infrastructure for using Cinelerra,
Part of this job was funded through the Fiduciary Fund
a community developed version of non-linear video editor.
of the Japan’s government - UNESCO with the program
As shown, this software could be used and employed by
Keizo Obuchi 2011-2012, and by FEDER funds and Xunta
educational institutions for teaching video techniques and to
de Galicia under project 09TIC001CT, contract 2010/28, and
create educational material. The main goal is to use, in a
by Spanish Government (MCYT) under project TEC2010-
more efficiently way, the computational resources managing
17320.
them as a virtual cloud infrastructure for rendering purposes.
This avoids the need of acquiring a rendering dedicated
hardware infrastructure allowing to reuse existing computer R EFERENCES
labs or desktop computers making them available to the
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