Fast data transfer technique for large data in grid environment

Nowadays, multimedia files such as videos and images are being improved in terms of their quality, where the dimension of the video or image is improving from two dimensional (2D) to become three or four dimensional (3D or 4D). These quality improvements have also increased the size of the multimedi...

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Main Author: Chong, Mien May
Format: Thesis
Language:English
Published: 2015
Online Access:http://psasir.upm.edu.my/id/eprint/57090/1/FSKTM%202015%203RR.pdf
http://psasir.upm.edu.my/id/eprint/57090/
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spelling my.upm.eprints.570902017-08-23T02:23:38Z http://psasir.upm.edu.my/id/eprint/57090/ Fast data transfer technique for large data in grid environment Chong, Mien May Nowadays, multimedia files such as videos and images are being improved in terms of their quality, where the dimension of the video or image is improving from two dimensional (2D) to become three or four dimensional (3D or 4D). These quality improvements have also increased the size of the multimedia data. Thus, the large size of video data has used a lot of time to transmit through the network. To solve the problem, in our research, we proposed a new video splitting technique, which is the "Exponential-and-Uniform-based (ExpoNUni) Splitting Technique" to improve the transmission time and maintain the quality of the data. Our "ExpoNUni" Splitting Technique has performed a better result compared to the existing techniques such as Fibonacci-based Splitting with V1min Technique and Uniform-based Splitting Technique. For the Initial Delay, overall, our splitting technique by average has 26.23 % lesser initial delay time for comparing with the existing Fibonacci-based Splitting with V1min Technique. It shows an 11.62% average of initial delay time lesser comparing to Uniform-based Splitting Technique.For download time, the overall result that compared with the existing Fibonacci-based Splitting with V1min Technique, our splitting technique by average 1.43% lesser time for downloading a complete video file to the user‘s PC from the grid storage, while the Uniform-based Splitting Technique, it shows 1.67% decrement of average downloading time. To prove the Exponential-and-Uniform-based splitter component is able to reduce the transmission time in a Grid-based Video Storage Framework, we also compare the uploading time and downloading time between the framework without the splitter component and the framework with our splitter component. The results show that the framework with our splitter component proofs it takes lesser data transmission time,where overall with an average of 9.86% lesser time for the uploading time and overall with an average of 12.24% lesser time for the downloading time. Besides, the MATLAB tool proves that our splitting technique did not affect the quality of the retrieved data. 2015-04 Thesis NonPeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/57090/1/FSKTM%202015%203RR.pdf Chong, Mien May (2015) Fast data transfer technique for large data in grid environment. Masters thesis, Universiti Putra Malaysia.
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Nowadays, multimedia files such as videos and images are being improved in terms of their quality, where the dimension of the video or image is improving from two dimensional (2D) to become three or four dimensional (3D or 4D). These quality improvements have also increased the size of the multimedia data. Thus, the large size of video data has used a lot of time to transmit through the network. To solve the problem, in our research, we proposed a new video splitting technique, which is the "Exponential-and-Uniform-based (ExpoNUni) Splitting Technique" to improve the transmission time and maintain the quality of the data. Our "ExpoNUni" Splitting Technique has performed a better result compared to the existing techniques such as Fibonacci-based Splitting with V1min Technique and Uniform-based Splitting Technique. For the Initial Delay, overall, our splitting technique by average has 26.23 % lesser initial delay time for comparing with the existing Fibonacci-based Splitting with V1min Technique. It shows an 11.62% average of initial delay time lesser comparing to Uniform-based Splitting Technique.For download time, the overall result that compared with the existing Fibonacci-based Splitting with V1min Technique, our splitting technique by average 1.43% lesser time for downloading a complete video file to the user‘s PC from the grid storage, while the Uniform-based Splitting Technique, it shows 1.67% decrement of average downloading time. To prove the Exponential-and-Uniform-based splitter component is able to reduce the transmission time in a Grid-based Video Storage Framework, we also compare the uploading time and downloading time between the framework without the splitter component and the framework with our splitter component. The results show that the framework with our splitter component proofs it takes lesser data transmission time,where overall with an average of 9.86% lesser time for the uploading time and overall with an average of 12.24% lesser time for the downloading time. Besides, the MATLAB tool proves that our splitting technique did not affect the quality of the retrieved data.
format Thesis
author Chong, Mien May
spellingShingle Chong, Mien May
Fast data transfer technique for large data in grid environment
author_facet Chong, Mien May
author_sort Chong, Mien May
title Fast data transfer technique for large data in grid environment
title_short Fast data transfer technique for large data in grid environment
title_full Fast data transfer technique for large data in grid environment
title_fullStr Fast data transfer technique for large data in grid environment
title_full_unstemmed Fast data transfer technique for large data in grid environment
title_sort fast data transfer technique for large data in grid environment
publishDate 2015
url http://psasir.upm.edu.my/id/eprint/57090/1/FSKTM%202015%203RR.pdf
http://psasir.upm.edu.my/id/eprint/57090/
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score 13.160551