International Journal of Engineering Trends and Technology- Volume4Issue3- 2013
Cloud Based E-Learning Platform Using
Dynamic Chunk Size
Dinoop M.S#1, Durga .S*2
PG Scholar, Karunya University
Assistant Professor, Karunya University
Abstract: E-learning is a tool which has the
potential to enhance and support the traditional
education method. This paper present and design
the novel approach for the e-learning video on
demand service using the new innovating
technology, cloud computing. For providing the
fast down loading and uploading of videos, high
security to the data, less consumption of band
width proposed approach using the dynamic
chunk size method.
I .INTRODUCTION
Structured learning[1] that is carried out
over an electronic platform is called e-learning. Elearning services can be divided in to Synchronous
and Asynchronous e-learning services[2]. In
synchronous e-learning system the students need to
be online at predefined time. Asynchronous elearning service can be accessed by the students
whenever they want. Four main components needed
for effective e-learning system are the participants,
facilitator, course design and technology support. Elearning service is provided for complete training or
to provide just in time information and expert
guidance. This paper describes a synchronous elearning system in which the students must be present
at the class time to get the streaming video tutorial
online.[3]Video on demand is one of the
advancements in the area of multimedia service using
which user can select and view the selected video.
Examples of applications of video on demand are
movies on Demand, E-Ecommerce, Interactive
advertisement etc. there are three types of playing
methods. They are download mode, streaming and
progressive download or pseudo streaming. In
download mode the downloaded video is played only
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after the complete download of the video. In
Streaming mode the video is downloaded in parts
andeach part is decoded and played before the
complete video is downloaded. In progressive
download the video is downloaded as in download
mode but the user can play the video if the download
speed is sufficiently greater than the playingrate.Main
issues in video on demand service are providing
sufficient bandwidth with low cost and security of
video content[4].There are many technologies that
can be used to provide e-learning video on demand
through internet. They can be traditional web based
technology, grid technology and cloud technology.
Connecting and integrating ideal system resources
with the application of proper operating system and
software are called grid computing technology. By
using this technique collection of sufficient
computing power for a super computer is generated.
[5]Providing computational power to a remote place
through a tcp/ip network such as internet is called
cloud computing. The main features of cloud
computing are location independent access,
competitively low deployment cost, scalability etc.
So this provides an effective system for providing elearning video on demand.
The challenges in providing an e-learning
system are Timing, Security, Bandwidth, Storage,
Quality of service etc. As explained in a synchronous
video on demand learning system the timing of
students and staffs are important. Security of video
content is important to avoid piracy. Sufficient
bandwidth is needed for an e-learning system. The
problem is we should expect scalability as the
number of students may ramp up any time.
Application of cloud technology can reduce this
problem. Storage space can be reduced by light
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International Journal of Engineering Trends and Technology- Volume4Issue3- 2013
weight storage and using efficient video compression
technique. The quality of service can be reduced by
the usage of Content Delivery Network (CDN).
are there are no interactive job submission and grid
software standards are still evolving.
III. PROPOSED WORK
The novel approach is based on the
progressive -learning , here we introduce the cloudbased e-learning for the increase of performance
,security ,and less bandwidth consumption.
II. RELATED WORKS
There are mainly three types of well-known
web based approaches. They are multi thread based,
RMI based and service oriented based. In 2011
DimitrisKarakasilisand et al.[6] proposed a method in
which python threads running over the server carries
out the functions of the video on demand system. We
can use a remote procedure from a remote place to
activate the video streaming.
P.Seethalakshmi and et al [7].proposed an
RMI based method. The clients can access the media
server at any time they want. Then a multimedia
environment is created by the server. This is done by
summing up the contents for each request and
starting a new thread for each of different content.
Valerie monfort and et al. proposed [8]a
service oriented architecture for e-learning. This
created interoperability between remote and local
homogenous and heterogeneous applications by using
reusable service logic.
This
provides a
standardization.
Kong Feng and et al. and Chao Tung and et
al. proposed[9] two different architectures for grid
based e-learning video on demand methods. This
method reduces the draw back in traditional web
based approach that is a highly loaded server. This
uses data grid and computational grid to fulfil the
needs for video on demand systems. This technology
integrates many video on demand nodes which solves
the storage as well as the computational needs of the
system.
Information service, file management,
resource scheduling, grid portal and content storage
are different components used in these systems to
provide a „video on demand distribution algorithm‟.
The advantages of the system are efficient usage of
resources and delivery of high computational power
and storage. The main disadvantages of these systems
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Novel approach is brings the traditional way
of learning in the new world in the new manner with
the help of cloud computing. The novel approach is
based on the progressive e-learning ,here we
introduce the cloud-based e-learning for the increase
of performance ,security ,and less bandwidth
consumption.
The performance cloud based e-learning
video on demand system can be increased by two
techniques. First Adaptive chunk size[10] and Second
Applying a light weight cloud storage engine. From
the performance analyses it is proved that if the
chunk size is increased then the upload time of the
video is decreased. So instead of using a fixed chunk
size we can calculate the server load and adaptively
change the chunk size. If the server load is high then
the chunk size is decreased and also if the server load
is low then the chunk size is increased.
Video capture
Video capture is the first step in the elearning. High definition quality cameras are used to
capture the sound and video. Thus they create a
virtual class room. The class room may be anywhere
in the world, the users of e-learning only require the
browser which support the internet connection. The
videos can upload only the register members of
cloud. In order to ensure the security and access
control to the data, clouds provide the biometric
authentication mechanism to the users. The following
diagram explains how the users can upload their data
in to cloud.
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To upload the data to the cloud , Server load
calculator first calculate the dynamic load of the
server. Then they divide the file size in to different
size of chunks according to the load of the server.
The different size of chunks is uploaded in to the
server. Dynamic chunk size of the file helps to
effectively store the data without the wastage of
storage.
Fig 1: Basic credential diagram
For uploading data to the cloud first the
user registers their details in to the cloud and obtains
the credentials for the further usage. Then the cloud
provider is stored the values on the database. When
the users want to upload the data in to the cloud first
they submit the value to the database. The cloud
provider is verifying that whether they submitted
value and the derived value are equal. If both the
values are equal then they allow uploading the value
in to the database.
Uploading
Video uploading can be done using the
cloud system. To provide the efficient storage of
cloud, our techniques using dynamic chunk size
method. The diagram shows the dynamic chunk size
method.
The files are stored using the blob concept.
In blob data are stored in the binary format. To
provide the integrity to the data for each blob storage
value‟s high security factor (HSF) is calculated and
stored with the files. The HSF is calculated by first
setting the middle factor value of the each row, then
xoring the first and last values for each row.
Down loading
The users for attending the class also
register with the cloud provider. The clod providers
give the credentials to the users. These are the second
category of the users in the e-learning, they are
attending the classes. The cloud provider update the
time of the class to the users. The videos are streamed
to the user‟s machine and they can easily watch and
users got the feeling that they are attending the real
classes without any interception .During the time of
streaming they check the HSF value of the blobs. If
the derived value of HSF is same as that of the
previous calculated value then the data stored in the
storage is the correct one and the integrity is
maintained. Otherwise the the data may be corrupted.
Analysis of Result
This section analysis the result of proposed
scheme with the fixed chunk sizes. In the fixed chunk
scheme the file is divided in to fixed size and stored
in the destination while in the dynamic loads the files
are stored on the basis of server loads.
Fig 2: Cloud Implementation diagram
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International Journal of Engineering Trends and Technology- Volume4Issue3- 2013
The diagram shows the download time
analysis of fixed and dynamic chunk sizes. The
dynamic chunk size has the less down load time
compared with the fixed one. The figure, shows for
fixed size of 32,64kb. The download time is less than
of 800 ms for various workloads. The down load time
graph is similar to the upload graph.
Fig 3: Upload time for 32Kb
The diagram shows the comparison between
the proposed system and the fixed chunk size. In
fixed chunk size the files are divided in to 32 kb and
uploaded. It takes higher time compared to the
proposed techniques. Whatever may be the file size it
have the increased upload time for the previous
method. The following diagram shows when we
divide the file in to fixed size of 64 kb. Fixed chunk
also have the same performance degradation
compared to the proposed method.
Fig 5: Download time for 32Kb
On the analysis of above graph clearly we
can found that the Dynamic chunk size having the
less down load time but the one problem is that it has
greater down load time when we upload the 25kb file
in the case of file divided with the 64kb sizes. But for
the 32kb fixed chunk size the proposed scheme has
the lesser down load time.
Fig 4: Upload time for 64 Kb
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International Journal of Engineering Trends and Technology- Volume4Issue3- 2013
IV. CONCLUSION
In this paper we havedesign, implemented
and presented the e-learning approach using Dynamic
chunk size. This method having the less download,
upload time .Server load calculation is helpful to
know the dynamic load of the system. When
compared this approach to other method it provide
the services to the users.
V. REFERENCE
Fig 6: Download time for 64 Kb
Scalability
Scalability in cloud computing is the ability
to accommodate the increase number of users. In elearning using dynamic chunk size able to provide
the services to the number of users. Proposed elearning method accommodate the increased number
of users with the higher security, performance etc.
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Fig 7: Scalability
The diagram shows the number of users v/s
performance degradation. For the dynamic chunk size
the performance degradation is less compared with
32kb fixed size.
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