The Design of Decomposed Learning Management System Based on Grid Structure

碩士 === 大葉大學 === 資訊工程學系碩士班 === 97 === This paper proposes an intelligent learning management system with load-balancing function based on Grid structure that allows for the replication of learning materials and balance of network traffic. The system consists of the Learning Management System (LMS) fo...

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Main Authors: Wen-Yu Chang, 張文瑜
Other Authors: Fu-Chien Kao
Format: Others
Language:zh-TW
Published: 2009
Online Access:http://ndltd.ncl.edu.tw/handle/52380518951205004200
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spelling ndltd-TW-097DYU003920132015-10-13T14:53:17Z http://ndltd.ncl.edu.tw/handle/52380518951205004200 The Design of Decomposed Learning Management System Based on Grid Structure 整合格網架構之分解式學習管理系統設計 Wen-Yu Chang 張文瑜 碩士 大葉大學 資訊工程學系碩士班 97 This paper proposes an intelligent learning management system with load-balancing function based on Grid structure that allows for the replication of learning materials and balance of network traffic. The system consists of the Learning Management System (LMS) for processing basic data, learning data and learning records of learners, and the Learning Content Management System (LCMS) based on the Grid structure for managing and storing the related teaching materials. The Web Service cross-platform distribution configuration of this research provides common communications between systems and enhances the capability of integrating learning resources. The Grid architecture of the system ensures a load-balancing functionality for LCMS of different domains. The learner via LMS connects to the Improved Ganglia Broker for access to required teaching materials from each LCMS. The LCMS with the minimum load is then selected from suitable LCMS as the source of the teaching materials. The proposed intelligent learning environment based on Grid structure is designed to improve the overload and the expansibility problems existing in the traditional decomposed LMS system. Fu-Chien Kao 高富建 2009 學位論文 ; thesis 0 zh-TW
collection NDLTD
language zh-TW
format Others
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description 碩士 === 大葉大學 === 資訊工程學系碩士班 === 97 === This paper proposes an intelligent learning management system with load-balancing function based on Grid structure that allows for the replication of learning materials and balance of network traffic. The system consists of the Learning Management System (LMS) for processing basic data, learning data and learning records of learners, and the Learning Content Management System (LCMS) based on the Grid structure for managing and storing the related teaching materials. The Web Service cross-platform distribution configuration of this research provides common communications between systems and enhances the capability of integrating learning resources. The Grid architecture of the system ensures a load-balancing functionality for LCMS of different domains. The learner via LMS connects to the Improved Ganglia Broker for access to required teaching materials from each LCMS. The LCMS with the minimum load is then selected from suitable LCMS as the source of the teaching materials. The proposed intelligent learning environment based on Grid structure is designed to improve the overload and the expansibility problems existing in the traditional decomposed LMS system.
author2 Fu-Chien Kao
author_facet Fu-Chien Kao
Wen-Yu Chang
張文瑜
author Wen-Yu Chang
張文瑜
spellingShingle Wen-Yu Chang
張文瑜
The Design of Decomposed Learning Management System Based on Grid Structure
author_sort Wen-Yu Chang
title The Design of Decomposed Learning Management System Based on Grid Structure
title_short The Design of Decomposed Learning Management System Based on Grid Structure
title_full The Design of Decomposed Learning Management System Based on Grid Structure
title_fullStr The Design of Decomposed Learning Management System Based on Grid Structure
title_full_unstemmed The Design of Decomposed Learning Management System Based on Grid Structure
title_sort the design of decomposed learning management system based on grid structure
publishDate 2009
url http://ndltd.ncl.edu.tw/handle/52380518951205004200
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