A model for client recommendation to a desktop grid server
A vast amount of idle computational power of desktop computers could be utilized throughout desktop grids. For an appropriate utilization, the scheduler, needs to determine clients which are best suited to deliver assigned jobs in time. Diversity of hosts (i.e. OS, hardware and network specification...
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Springer
2013
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Online Access: | http://psasir.upm.edu.my/id/eprint/60358/1/A%20model%20for%20client%20recommendation%20to%20a%20desktop%20grid%20server.pdf http://psasir.upm.edu.my/id/eprint/60358/ |
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my.upm.eprints.603582018-05-21T03:27:35Z http://psasir.upm.edu.my/id/eprint/60358/ A model for client recommendation to a desktop grid server Shafazand, Mohammad Yaser Latip, Rohaya Abdullah, Azizol Hussin, Masnida A vast amount of idle computational power of desktop computers could be utilized throughout desktop grids. For an appropriate utilization, the scheduler, needs to determine clients which are best suited to deliver assigned jobs in time. Diversity of hosts (i.e. OS, hardware and network specifications) and intermittent availability of resources are known issues which complicate the schedulers work. As a solution to this problem, a client–server model consisting two modules for a desktop grid middleware is discussed: a module to forecast machine resource availability in the client side and a module in the server side that recommends clients to the scheduler that are the nearest to job expectations. Historic data, time-series analyses and machine learning are used for this purpose in the modules. Springer 2013 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/60358/1/A%20model%20for%20client%20recommendation%20to%20a%20desktop%20grid%20server.pdf Shafazand, Mohammad Yaser and Latip, Rohaya and Abdullah, Azizol and Hussin, Masnida (2013) A model for client recommendation to a desktop grid server. In: First International Conference on Advanced Data and Information Engineering (DaEng-2013), 16-18 Dec. 2013, Kuala Lumpur, Malaysia. (pp. 491-498). 10.1007/978-981-4585-18-7_55 |
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A vast amount of idle computational power of desktop computers could be utilized throughout desktop grids. For an appropriate utilization, the scheduler, needs to determine clients which are best suited to deliver assigned jobs in time. Diversity of hosts (i.e. OS, hardware and network specifications) and intermittent availability of resources are known issues which complicate the schedulers work. As a solution to this problem, a client–server model consisting two modules for a desktop grid middleware is discussed: a module to forecast machine resource availability in the client side and a module in the server side that recommends clients to the scheduler that are the nearest to job expectations. Historic data, time-series analyses and machine learning are used for this purpose in the modules. |
format |
Conference or Workshop Item |
author |
Shafazand, Mohammad Yaser Latip, Rohaya Abdullah, Azizol Hussin, Masnida |
spellingShingle |
Shafazand, Mohammad Yaser Latip, Rohaya Abdullah, Azizol Hussin, Masnida A model for client recommendation to a desktop grid server |
author_facet |
Shafazand, Mohammad Yaser Latip, Rohaya Abdullah, Azizol Hussin, Masnida |
author_sort |
Shafazand, Mohammad Yaser |
title |
A model for client recommendation to a desktop grid server |
title_short |
A model for client recommendation to a desktop grid server |
title_full |
A model for client recommendation to a desktop grid server |
title_fullStr |
A model for client recommendation to a desktop grid server |
title_full_unstemmed |
A model for client recommendation to a desktop grid server |
title_sort |
model for client recommendation to a desktop grid server |
publisher |
Springer |
publishDate |
2013 |
url |
http://psasir.upm.edu.my/id/eprint/60358/1/A%20model%20for%20client%20recommendation%20to%20a%20desktop%20grid%20server.pdf http://psasir.upm.edu.my/id/eprint/60358/ |
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