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Cluster Computing and the Grid, IEEE International Symposium on (2011)
Newport Beach, California USA
May 23, 2011 to May 26, 2011
ISBN: 978-0-7695-4395-6
pp: 124-133
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.
grid, behavior prediction

M. S. Pérez, J. Montes and A. S´nchez, "Grid Global Behavior Prediction," Cluster Computing and the Grid, IEEE International Symposium on(CCGRID), Newport Beach, California USA, 2011, pp. 124-133.
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