DocumentCode
1943522
Title
A Novel Adaptive Neuro Fuzzy Inference System Based CPU Scheduler for Multimedia Operating System
Author
Atique, Mohammad ; Ali, Mir Sadique
Author_Institution
Gov. Coll. of Eng., Amravati
fYear
2007
fDate
12-17 Aug. 2007
Firstpage
1002
Lastpage
1007
Abstract
In this paper we propose a novel CPU Scheduler based on Adaptive Neuro Fuzzy Inference System (ANFIS), to support the execution of multimedia applications along with conventional applications in multimedia operating system. Adaptive Neuro-Fuzzy Inference System (ANFIS) can be used to solve highly non-linear dynamic problems. This paper shows how an ANFIS can be used to optimize CPU scheduling in multimedia operating system. This adaptive intelligent scheduler should be considered as middle layer software, aware of current available resources. This scheduler takes decision based on the past experiences. We have used ANFIS architecture, which is able to cluster the data distributed in a multi dimensional input space using a set of fuzzy rules. A simulator is developed in Matlab 7.2.0.232 and the performance of the proposed scheduler is evaluated against the existing algorithms. It is demonstrated that, the proposed scheduler is able to optimize various CPU scheduling parameters as well as resource utilization.
Keywords
fuzzy neural nets; fuzzy reasoning; fuzzy set theory; multimedia systems; operating systems (computers); optimisation; resource allocation; scheduling; CPU scheduling; adaptive neuro fuzzy inference system; fuzzy rule set; middle layer software; multimedia operating system; nonlinear dynamic problem; optimization; resource utilization; Adaptive scheduling; Adaptive systems; Application software; Computer architecture; Fuzzy sets; Fuzzy systems; Intelligent systems; Multimedia systems; Nonlinear dynamical systems; Operating systems;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2007. IJCNN 2007. International Joint Conference on
Conference_Location
Orlando, FL
ISSN
1098-7576
Print_ISBN
978-1-4244-1379-9
Electronic_ISBN
1098-7576
Type
conf
DOI
10.1109/IJCNN.2007.4371095
Filename
4371095
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