Aplicación de un Clúster de Máquinas Físicas y Virtuales para la reducción de tiempo de Segmentación en la Clasificación de Imágenes Satelitales utilizando Computación Paralela y Redes Neuronales

Published in: Innovation in Education and Inclusion : Proceedings of the 16th LACCEI International Multi-Conference for Engineering, Education and Technology
Date of Conference: July 18-20, 2018
Location of Conference: Lima, Perú
Authors: Yoni Huaynacho Peñaloza (Universidad Nacional de San Agustín de Arequipa, PE)
Abel Huaynacho Peñaloza (Universidad Nacional de San Agustín de Arequipa, PE)
Pablo Raúl Yanyachi Aco-Cardenas(Universidad Nacional de San Agustín de Arequipa)
Full Paper: #514

Abstract:

There are different projects, theses, articles and others that need a cluster of computers for testing with a large number of machines. The students , investigators and others don't have many machines to study in the big data field In addition if you get machines usually have different Operating system, processor, hard disk and others. A very important issue is to reduce the time to classify satellite images that have very high data sizes and when they are processed the computer becomes slow. For all this, it article use virtual machines as a solution, these are used to test the reduction of response times in the classification of satellite images using also a classification tool with neural networks. As a result of this article we have tested qualifying 1000000 lines of dates in sequential form and as distributed form using virtual machines to compare response times.