Load Allocation Model for Scheduling Divisible Data Grid Applications

Abstract

Problem statement: In many data grid applications, data can be decomposed into multiple independent sub-datasets and distributed for parallel execution and analysis. Approach: This property had been successfully employed by using Divisible Load Theory (DLT), which had been proved as a powerful tool for modeling divisible load problems in data-intensive grid. Results: There were some scheduling models had been studied but no optimal solution has been reached due to the heterogeneity of the grids. This study proposed a new optimal load allocation based on DLT model recursive numerical closed form solutions are derived to find the optimal workload assigned to the processing nodes. Conclusion/Recommendations: Experimental results showed that the proposed model obtained better solution than other models (almost optimal) in terms of Makespan.