ISSN : 1796-203X
Volume : 3    Issue : 12    Date : December 2008

Scheduling Algorithm with Potential Behaviors
Jianhua Jiang, Huifang Ji, Gaochao Xu, and Xiaohui Wei
Page(s): 51-59
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Scheduling algorithm for batch-mode data-intensive jobs is a key issue in data-intensive Grid
applications. It focuses on how to minimize the overhead of transferring the required data set to the
executing grid site. Existing approaches pay attention to the access cost of a data-intensive job at
each executing grid site for replicating the required data set. However, they neglect the influence
from potential behaviors of jobs in the waiting queue at each grid site when the access cost is
evaluated. In this paper, we consider the influence of potential behaviors on the access cost, and
propose a data-intensive job scheduling algorithm with potential behaviors. Furthermore, the
causation of potential behaviors is analyzed. The simulation result in OptorSim shows that it has
better performance in mean job time of all jobs, total number of replications, total number of local
files accesses and effective network usage than the scheduling algorithm based on access cost.

Index Terms
distributed computing, grid computing, data grid, job scheduling, access cost, replica replacement