Adaptive Divisible Load Model for Scheduling Data-Intensive Grid Applications

Authors:
M. Othman;M. Abdullah;H. Ibrahim;S. Subramaniam
Affiliations:
Department of Communication Technology and Network, Faculty of Computer Science and Information Technology, University Putra Malaysia, 43400 UPM Serdang, Selangor D.E., Malaysia;Department of Communication Technology and Network, Faculty of Computer Science and Information Technology, University Putra Malaysia, 43400 UPM Serdang, Selangor D.E., Malaysia;Department of Communication Technology and Network, Faculty of Computer Science and Information Technology, University Putra Malaysia, 43400 UPM Serdang, Selangor D.E., Malaysia;Department of Communication Technology and Network, Faculty of Computer Science and Information Technology, University Putra Malaysia, 43400 UPM Serdang, Selangor D.E., Malaysia
Venue:
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007
Year:
2007

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Abstract

In many data grid applications, data can be decomposed into multiple independent sub datasets and schedule for parallel execution and analysis. Divisible Load Theory (DLT) is a powerful tool for modelling data-intensive grid problems where both communication and computation load is partitionable. This paper presents an Adaptive DLT (ADLT) model for scheduling data-intensive grid applications. This model reduces the expected processing time approximately 80% for communication intensive applications and 60% for computation intensive applications compared to the previous DLT model. Experimental results show that this model can balance the loads efficiently.