The Map-Reduce Parallelism Framework for Task Scheduling in Grid Computing
2011 ◽
Vol 216
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pp. 111-115
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Keyword(s):
As a rapid developing infrastructure, the grid can share widely distributed computing, storage, data and human resources. In order to improve the usability and QoS of the grid, the job management in the grid is very important, and becomes one of the key research issues in grid computing. Map-Reduce provide an efficient and easy-to-use framework for parallelizing the global optimization procedure. The simulation results show the usefulness and effectiveness of our task scheduling algorithm.
2011 ◽
Vol 04
(04)
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pp. 227-231
Keyword(s):
2020 ◽
Vol 16
(3)
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pp. 287
Keyword(s):
2009 ◽
Vol 31
(4)
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pp. 713-722
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Keyword(s):
2011 ◽
Vol 50-51
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pp. 526-530
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Keyword(s):
2014 ◽
Vol 577
◽
pp. 935-938
Keyword(s):