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DOI: 10.14569/IJACSA.2017.080214
PDF

Efficient Model for Distributed Computing based on Smart Embedded Agent

Author 1: Hassna Bensag
Author 2: Mohamed Youssfi
Author 3: Omar Bouattane

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 2, 2017.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: Technological advances of embedded computing exposed humans to an increasing intrusion of computing in their day-to-day life (e.g. smart devices). Cooperation, autonomy, and mobility made the agent a promising mechanism for embedded devices. The work aims to present a new model of an embedded agent designed to be implemented in smart devices in order to achieve parallel tasks in a distribute environment. To validate the proposed model, a case study was developed for medical image segmentation using Cardiac Magnetic Resonance Image (MRI). In the first part of this paper, we focus on implementing the parallel algorithm of classification using C-means method in embedded systems. We propose then a new concept of distributed classification using multi-agent systems based on JADE and Raspberry PI 2 devices.

Keywords: Distributed computing; parallel computing; Multi Agent System; Embedded computing; Raspberry PI 2

Hassna Bensag, Mohamed Youssfi and Omar Bouattane, “Efficient Model for Distributed Computing based on Smart Embedded Agent” International Journal of Advanced Computer Science and Applications(IJACSA), 8(2), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080214

@article{Bensag2017,
title = {Efficient Model for Distributed Computing based on Smart Embedded Agent},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080214},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080214},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {2},
author = {Hassna Bensag and Mohamed Youssfi and Omar Bouattane}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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