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All Journal International Journal of Electrical and Computer Engineering
El Amrani Chaker
Abdelmalek Essaadi University, Morocco
Computer Science & IT Electrical & Electronics Engineering

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Comparative Study of Neural Networks Algorithms for Cloud Computing CPU Scheduling Gibet Tani Hicham; El Amrani Chaker; Elaachak Lotfi
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 6: December 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (526.285 KB) | DOI: 10.11591/ijece.v7i6.pp3570-3577

Abstract

Cloud Computing is the most powerful computing model of our time. While the major IT providers and consumers are competing to exploit the benefits of this computing model in order to thrive their profits, most of the cloud computing platforms are still built on operating systems that uses basic CPU (Core Processing Unit) scheduling algorithms that lacks the intelligence needed for such innovative computing model. Correspdondingly, this paper presents the benefits of applying Artificial Neural Networks algorithms in regards to enhancing CPU scheduling for Cloud Computing model. Furthermore, a set of characteristics and theoretical metrics are proposed for the sake of comparing the different Artificial Neural Networks algorithms and finding the most accurate algorithm for Cloud Computing CPU Scheduling.
Co-Authors Elaachak Lotfi Gibet Tani Hicham