Title: An adaptive meta-scheduler for data-intensive applications

Authors: Hai Jin, Xuanhua Shi, Weizhong Qiang, Deqing Zou

Addresses: Cluster and Grid Computing Lab, Huazhong University of Science and Technology, Wuhan 430074, China. ' Cluster and Grid Computing Lab, Huazhong University of Science and Technology, Wuhan 430074, China. ' Cluster and Grid Computing Lab, Huazhong University of Science and Technology, Wuhan 430074, China. ' Cluster and Grid Computing Lab, Huazhong University of Science and Technology, Wuhan 430074, China

Abstract: In data-intensive applications, such as high-energy physics, bio-informatics, we encounter applications involving numerous jobs that access and generate large datasets. Effective scheduling of such applications is a challenge, due to the need to consider for both computational resources and data storage resources. In this paper, we describe an adaptive scheduling model that considers availability of computational, storage and network resources. Based on this model we implement a scheduler used in our campus grid. The results achieved by our scheduler have been analysed by comparing with greedy algorithm that is widely used in computational grids and some data grids.

Keywords: grid computing; adaptive scheduling; task scheduling; metascheduler; replication; computational grids; data grids; greedy scheduling algorithm; scientific computing; high-energy physics; bioinformatics; data storage; network resources; computational resources.

DOI: 10.1504/IJGUC.2005.007058

International Journal of Grid and Utility Computing, 2005 Vol.1 No.1, pp.32 - 37

Published online: 16 May 2005 *

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