A neural network realization of scheduling in grid computing environment

Authors:
Mohammad Kalantari;Kazem Akbari
Affiliations:
Computer Engineering Department, Amirkabir University of Technology, Tehran Polytechnic, Tehran, Iran;Computer Engineering Department, Amirkabir University of Technology, Tehran Polytechnic, Tehran, Iran
Venue:
SMO'05 Proceedings of the 5th WSEAS international conference on Simulation, modelling and optimization
Year:
2005

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Abstract

The Computational Grids provide a promising platform for efficient execution of computational and data intensive applications. Scheduling in such environments is challenging because target resources are heterogeneous and their load and availability varies dynamically. In this paper, we propose a mathematical neural network based scheduling solution for grid computing environment. Using mathematical method guarantees rapid convergenc that is essential for such environments with proliferation of resources.