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DIANA Scheduling Hierarchies for Optimizing Bulk Job Scheduling

Anjum, Ashiq and McClatchey, Richard and Stockinger, Heinz and Ali, Arshad and Willers, Ian and Thomas, Michael and Sagheer, Muhammad and Hasham, Khawar and Alvi, Omer (2006) DIANA Scheduling Hierarchies for Optimizing Bulk Job Scheduling. In: 2006 Second IEEE International Conference on e-Science and Grid Computing (e-Science'06). IEEE , Piscataway, NJ, p. 89. ISBN 0-7695-2734-5.

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The use of meta-schedulers for resource management in large-scale distributed systems often leads to a hierarchy of schedulers. In this paper, we discuss why existing meta-scheduling hierarchies are sometimes not sufficient for Grid systems due to their inability to re-organise jobs already scheduled locally. Such a job re-organisation is required to adapt to evolving loads which are common in heavily used Grid infrastructures. We propose a peer-topeer scheduling model and evaluate it using case studies and mathematical modelling. We detail the DIANA (Data Intensive and Network Aware) scheduling algorithm and its queue management system for coping with the load distribution and for supporting bulk job scheduling. We demonstrate that such a system is beneficial for dynamic, distributed and self-organizing resource management and can assist in optimizing load or job distribution in complex Grid infrastructures.

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Additional Information:© 2006 IEEE.
Record Number:CaltechAUTHORS:20170427-145030435
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Official Citation:A. Anjum et al., "DIANA Scheduling Hierarchies for Optimizing Bulk Job Scheduling," 2006 Second IEEE International Conference on e-Science and Grid Computing (e-Science'06), Amsterdam, The Netherlands, 2006, pp. 89-89. doi: 10.1109/E-SCIENCE.2006.261173
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:77022
Deposited On:27 Apr 2017 22:06
Last Modified:15 Nov 2021 17:04

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