A features based expert artificial neural networks scheduling system
Author
Source
International Journal of Intelligent Computing and Information Sciences
Issue
Vol. 7, Issue 2 (31 Jul. 2007)12 p.
Publisher
Ain Shams University Faculty of Computer and Information Sciences
Publication Date
2007-07-31
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Information Technology and Computer Science
Topics
Abstract EN
Scheduling problems are one of the most challenging problems that can utilize the rapid improvements in parallel computer architectures.
In the context of scheduling, the problem is to exploit all the available resources of the available parallel architecture and optimize the target performance measure(s) or scheduling criteria.
The research work presented in this paper is motivated by the fact that there is no optimal scheduling approach due to the NP-complete nature of scheduling problems.
Moreover, the fact that scheduling of any problem on parallel / distributed platform is dependent on all the available inputs / features of that problem.
This paper introduces a scheduling model based on utilizing all available features that can be extracted from the problem then using them as inputs to a suite of expert artificial neural network architectures.
The proposed system was tested on a benchmark-scheduling problem in addition to a real time scheduling problem.
Regardless of its innovative set of features, and its unique architecture, the proposed system was compared with three other systems.
The experimental results showed that the proposed system improved the scheduling speedup of the given problems by 12% over the best of the other three systems.
In addition, the proposed system did not only enhanced the given problem performance measures but it did decrease the number of required processing elements and hence computational processing power for this real world problem.
American Psychological Association (APA)
Taha, Inas A.. 2007. A features based expert artificial neural networks scheduling system. International Journal of Intelligent Computing and Information Sciences،Vol. 7, no. 2.
https://search.emarefa.net/detail/BIM-284868
Modern Language Association (MLA)
Taha, Inas A.. A features based expert artificial neural networks scheduling system. International Journal of Intelligent Computing and Information Sciences Vol. 7, no. 2 (Jul. 2007).
https://search.emarefa.net/detail/BIM-284868
American Medical Association (AMA)
Taha, Inas A.. A features based expert artificial neural networks scheduling system. International Journal of Intelligent Computing and Information Sciences. 2007. Vol. 7, no. 2.
https://search.emarefa.net/detail/BIM-284868
Data Type
Journal Articles
Language
English
Notes
Includes appendices.
Record ID
BIM-284868