Process Harmonization of Objects for Learning Grid Computing Environment
G.Manoharan1, K.Nirmala2

1G.Manoharan, Research Scholar, Manonmanium Sundararar University, Tirunel Veli, India.
2Dr. K. Nirmala, Associate Prof., Dept. of Comp Science, Quide-E-Millath-College for Woman, Chennai, India.

Manuscript received on October 11, 2013. | Revised Manuscript received on October 15, 2013. | Manuscript published on October 25, 2013. | PP:47-50 | Volume-1, Issue-12, October 2013. | Retrieval Number: L05231011213/2013©BEIESP

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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Advancements in computing and internet technologies have made it possible to share data storage and data transfer resources, and computing power that are distributed across the world in networks. This opportunity has led to the development of a distributed computing environment called ‘Grid computing’ or ‘Grid’. Research publications are aplenty on methodologies and approaches for sharing such resources in Grids. Massive creation added with reduced cost has made rich education contents to explore avenues such as Education Grids or Education Cloud Computing. However, issues such as heterogeneity and task scheduling with respect to load balancing have become complex research problems that need to be addressed. Educational e-contents are highly heterogeneous in regard to processing sizes. Therefore uniform load balancing on e-Learning jobs in Grids may not be completely achievable. However, it is found from literature that load harmonization with respect to variety of computing resources have been tried out. Instructional modules in e-Learning environments are generally available in independent entities called ‘Objects’ of different volumes and computational intensities that use different variety of computing resources. This paper presents parametric representations of user requests, for Harmonizing Learning Objects in Grid Computing Environment. These parametric representations would be useful for effective Grid scheduling that applies semantics and also for modeling semantic grid.
Keywords: Technology Enhanced Learning, Education Grids, Virtual Organization, Semantic representation.