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Memorias de investigación
Communications at congresses:
Grid Global Behavior Prediction
Year:2011
Research Areas
  • Computer systems
Information
Abstract
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.
International
Si
Congress
11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing
960
Place
Newport Beach, CA
Reviewers
Si
ISBN/ISSN
978-1-4577-0129-0
10.1109/CCGrid.2011.17
Start Date
23/05/2011
End Date
25/05/2011
From page
124
To page
133
Cluster, Cloud and Grid Computing (CCGrid), 2011 11th IEEE/ACM International Symposium on
Participants
  • Autor: Jesús Montes
  • Autor: Alberto Sánchez
  • Autor: Maria de los Santos Perez Hernandez (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Ontology Engineering Group
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