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Task scheduling scheme based on resource clustering in desktop grids

Desktop grids are platforms for grid computing that incorporate desktop resources into a grid infrastructure. The purpose of this computing paradigm is to process a massive computational tasks by exploiting the donated resources connected over the Internet. In desktop grids, it is important to guarantee fast turnaround time in the presence of dynamic properties, such as volatility and heterogeneity. To achieve this objective, we propose a task scheduling scheme based on resource clustering that can selectively allocate tasks to those resources that are most suitable for the current situation of a desktop grid environment. As a classifier of resources, the k‐means clustering algorithm is introduced to classify resources according to their own task execution availability and result‐return probability. The experimental results show that our scheduling scheme is more efficient than existing scheduling schemes with respect to reducing both the turnaround time and the quantity of resources consumed. Copyright © 2013 John Wiley & Sons, Ltd.