Grades Computacionais Oportunistas: Alternativas para Melhorar o Desempenho das Aplicações

• Autor(a) principal: GOMES, Raphael de Aquino
• Data de Publicação: 2009
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional da UFG
• Texto Completo: http://repositorio.bc.ufg.br/tede/handle/tde/524
• topic: Computação em Grade, Grades Oportunistas, Desempenho, InteGrade; Grid Computing, Scavenging Grid, Performance, InteGrade; CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::SISTEMAS DE COMPUTACAO

Scavenging grid computing environments are being even more used as an alternative aside traditional processing categories. This kind of system is characterized by using of communal and shared workstations and its main concern is the guarantee of performance for the user who gives its resources to the grid. This concern, and because it is an extremaly dynamic environment, causes the adoption of treatments limited to best-effort. However, this effort hardly ever is fulfilled in an optimal way due the fact that are usually used treatments which doesn t create an effective managing of resources, doing the competitiveness of the grid applications with the local applications always penalize the grid s tasks, lowing the its performance. This work presents an architecture for the performance improvement to the grid applications, which takes into account using profiles of resources for locals applications, trying to identify when it is temporary and avoid taking actions as grid tasks migration. As alternative way or additional is proposed the using of adaptive technics who focus allowing the grade tasks maintenance on the actual node or the system improvement. The architecture was partially implemented on InteGrade middleware. We describe the developed implementation an its evaluation