DCA - Departamento de Engenharia de Computação
URI Permanente desta comunidadehttps://repositorio.ufrn.br/handle/1/128
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Navegando DCA - Departamento de Engenharia de Computação por Autor "Aroca, Rafael Vidal"
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Artigo NPi-Cluster: a Low Power Energy-Proportional Computing Cluster Architecture(Institute of Electrical and Electronics Engineers, 2017-08-09) Filho, Sebastião Emidio Alves; Burlamaqui, Aquiles Medeiros Filgueira; Aroca, Rafael Vidal; Gonçalves, Luiz Marcos GarciaThis paper presents the NPi-Cluster, an energy proportional computing cluster that automatically powers ON or OFF the number of running machines according to the actual processing demand. A theoretical model is proposed, discussed, and implemented on a cluster composed of Raspberry Pi computer boards designed and built in order to test the proposed system architecture. Experimental results show adequate performance of the proposed platform when compared with other web servers running on traditional server architectures, but with considerably less power consumption. The power consumption of the entire cluster is about 14 W when running at maximum performance. In this situation, the system is able to handle more than 450 simultaneous requests, with about 1000 transactions per second, making it possible to be used as a server capable of handling real web workloads with acceptable quality of service. When the requests demand is reduced to a minimum, the power consumption is dynamically reduced until less than 2 W. Additionally, the proposed cluster architecture also provides high availability by reducing single points of failure on the systemArtigo A wearable mobile sensor platform to assist fruit grading(MDPI, 2013-05-10) Aroca, Rafael Vidal; Gomes, Rafael Beserra; Dantas, Rummenigge Rudson; Calbo, Adonai G.; Gonçalves, Luiz Marcos GarciaWearable computing is a form of ubiquitous computing that offers flexible and useful tools for users. Specifically, glove-based systems have been used in the last 30 years in a variety of applications, but mostly focusing on sensing people’s attributes, such as finger bending and heart rate. In contrast, we propose in this work a novel flexible and reconfigurable instrumentation platform in the form of a glove, which can be used to analyze and measure attributes of fruits by just pointing or touching them with the proposed glove. An architecture for such a platform is designed and its application for intuitive fruit grading is also presented, including experimental results for several fruits