Efficient Model for Distributed Computing based on Smart Embedded Agent

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.