MaGate Simulator: A Simulation Environment for a Decentralized Grid Scheduler

Authors:
Ye Huang;Amos Brocco;Michele Courant;Beat Hirsbrunner;Pierre Kuonen
Affiliations:
Department of Informatics, University of Fribourg, Switzerland, Department of Information and Communication Technologies, University of Applied Sciences Western Switzerland (Fribourg),;Department of Informatics, University of Fribourg, Switzerland, Department of Information and Communication Technologies, University of Applied Sciences Western Switzerland (Fribourg),;Department of Informatics, University of Fribourg, Switzerland, Department of Information and Communication Technologies, University of Applied Sciences Western Switzerland (Fribourg),;Department of Informatics, University of Fribourg, Switzerland, Department of Information and Communication Technologies, University of Applied Sciences Western Switzerland (Fribourg),;Department of Informatics, University of Fribourg, Switzerland, Department of Information and Communication Technologies, University of Applied Sciences Western Switzerland (Fribourg),
Venue:
APPT '09 Proceedings of the 8th International Symposium on Advanced Parallel Processing Technologies
Year:
2009

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Abstract

This paper presents a simulator for of a decentralized modular grid scheduler named MaGate. MaGate's design emphasizes scheduler interoperability by providing intelligent scheduling serving the grid community as a whole. Each MaGate scheduler instance is able to deal with dynamic scheduling conditions, with continuously arriving grid jobs. Received jobs are either allocated on local resources, or delegated to other MaGates for remote execution. The proposed MaGate simulator is based on GridSim toolkit and Alea simulator, and abstracts the features and behaviors of complex fundamental grid elements, such as grid jobs, grid resources, and grid users. Simulation of scheduling tasks is supported by a grid network overlay simulator executing distributed ant-based swarm intelligence algorithms to provide services such as group communication and resource discovery. For evaluation, a comparison of behaviors of different collaborative policies among a community of MaGates is provided. Results support the use of the proposed approach as a functional ready grid scheduler simulator.