Memorias de investigación
Ponencias en congresos:
Grid Global Behavior Prediction
Año:2011
Áreas de investigación
  • Informática
Datos
Descripción
Complexity has always been one of the most important issues in distributed computing. From the first clusters to grid and now cloud computing, dealing correctly and efficiently with system complexity is the key to taking technology a step further. In this sense, global behavior modeling is an innovative methodology aimed at understanding the grid behavior. The main objective of this methodology is to synthesize the grid's vast, heterogeneous nature into a simple but powerful behavior model, represented in the form of a single, abstract entity, with a global state. Global behavior modeling has proved to be very useful in effectively managing grid complexity but, in many cases, deeper knowledge is needed. It generates a descriptive model that could be greatly improved if extended not only to explain behavior, but also to predict it. In this paper we present a prediction methodology whose objective is to define the techniques needed to create global behavior prediction models for grid systems. This global behavior prediction can benefit grid management, specially in areas such as fault tolerance or job scheduling. The paper presents experimental results obtained in real scenarios in order to validate this approach.
Internacional
Si
Nombre congreso
11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing
Tipo de participación
960
Lugar del congreso
Newport Beach, CA
Revisores
Si
ISBN o ISSN
978-1-4577-0129-0
DOI
10.1109/CCGrid.2011.17
Fecha inicio congreso
23/05/2011
Fecha fin congreso
25/05/2011
Desde la página
124
Hasta la página
133
Título de las actas
Cluster, Cloud and Grid Computing (CCGrid), 2011 11th IEEE/ACM International Symposium on
Esta actividad pertenece a memorias de investigación
Participantes
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Ontology Engineering Group