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Computers 2016, 5(3), 14; doi:10.3390/computers5030014

A New Scalable, Distributed, Fuzzy C-Means Algorithm-Based Mobile Agents Scheme for HPC: SPMD Application

Laboratory SSDIA, ENSET Mohammedia, Hassan II University of Casablanca, Mohammedia 28999, Morocco
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Author to whom correspondence should be addressed.
Academic Editor: José Luis Vázquez-Poletti
Received: 4 May 2016 / Revised: 29 June 2016 / Accepted: 1 July 2016 / Published: 11 July 2016
(This article belongs to the Special Issue High Performance Computing for Big Data)
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Abstract

The aim of this paper is to present a mobile agents model for distributed classification of Big Data. The great challenge is to optimize the communication costs between the processing elements (PEs) in the parallel and distributed computational models by the way to ensure the scalability and the efficiency of this method. Additionally, the proposed distributed method integrates a new communication mechanism to ensure HPC (High Performance Computing) of parallel programs as distributed one, by means of cooperative mobile agents team that uses its asynchronous communication ability to achieve that. This mobile agents team implements the distributed method of the Fuzzy C-Means Algorithm (DFCM) and performs the Big Data classification in the distributed system. The paper shows the proposed scheme and its assigned DFCM algorithm and presents some experimental results that illustrate the scalability and the efficiency of this distributed method. View Full-Text
Keywords: Fuzzy C-Means algorithm; parallel and distributed computing; distributed classification; MRI Big Data analysis; Multi Agent System; mobile agent Fuzzy C-Means algorithm; parallel and distributed computing; distributed classification; MRI Big Data analysis; Multi Agent System; mobile agent
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MDPI and ACS Style

Benchara, F.Z.; Youssfi, M.; Bouattane, O.; Ouajji, H. A New Scalable, Distributed, Fuzzy C-Means Algorithm-Based Mobile Agents Scheme for HPC: SPMD Application. Computers 2016, 5, 14.

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