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     Research Journal of Applied Sciences, Engineering and Technology


Optimized Grid Based e-Learning Framework

1Suresh Jaganathan, 2Srinivasan Arulanandam and 3A. Damodaram
1Department of Computer Science and Engineering, SSN College of Engineering, Anna University
2Department of Information Technology, MNM Jain Engineering College, Anna University, Chennai
3Department of Computer Science and Engineering, Jawaharlal Nehru Technological University, Hyderabad, Telugana, India
Research Journal of Applied Sciences, Engineering and Technology  2014  22:2290-2299
http://dx.doi.org/10.19026/rjaset.8.1231  |  © The Author(s) 2014
Received: September ‎13, ‎2014  |  Accepted: ‎September ‎20, ‎2014  |  Published: December 15, 2014

Abstract

E-Learning is the process of extending the resources to different locations by using multimedia communications. Many e-Learning methodologies are available and based on client-server, peer-to-peer and using Grid Computing concepts. To establish e-Learning process, systems should satisfy these needs, i) high storage for storing, ii) high network throughput for faster transfer and iii) efficient streaming of materials. The first and second needs are satisfied by using Grid and P2P technologies and the third need can be achieved by an efficient video compression algorithm. This study proposes a framework, called Optimized Grid Based e-Learning (OgBeL), which adopts both Grid and P2P technology. To reduce the e-Learning material size for efficient streaming, a light weight compression algorithm called dWave is embedded in OgBeL. The behavior of framework is analyzed in terms of time taken to transfer files using in-use grid protocols and in networks combined with grid and P2P.

Keywords:

Distributed networks, education, e-learning, grid computing, multimedia streaming, peer-to-peer networks , wireless networks,


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Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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