Pervasive Grid computing platforms are com- posed of a variety of fixed and mobile nodes, interconnected through multiple wireless and wired network technologies. Pervasive Grid Applications must adapt themselves to the state of their surrounding environment which includes envi- ronmental data (e.g. collected from sensors) and the state of the used resources (e.g. network or node states). Adaptation is especially important if we consider complex High-Performance Pervasive Grid applications, such as intelligent transportation and emergency management. In this paper we investigate how to define adaptivity for complex Pervasive Grid applications by providing multiple versions of application parallel modules. The versions are defined by exploiting different sequential algorithms and parallelization techniques. We introduce per- formance analysis tools for versions, which allow us to define specific selection policies of the best version to be executed, depending on the context. We show how each version is best suited to be executed on two application scenarios, also by means of experiments. To synthesize the contributions of this paper we introduce the ASSISTANT programming model, for adaptive Pervasive Grid applications.

Adaptivity in Risk and Emergency Management Applications on Pervasive Grids

BERTOLLI, CARLO;MENCAGLI, GABRIELE;VANNESCHI, MARCO
2009

Abstract

Pervasive Grid computing platforms are com- posed of a variety of fixed and mobile nodes, interconnected through multiple wireless and wired network technologies. Pervasive Grid Applications must adapt themselves to the state of their surrounding environment which includes envi- ronmental data (e.g. collected from sensors) and the state of the used resources (e.g. network or node states). Adaptation is especially important if we consider complex High-Performance Pervasive Grid applications, such as intelligent transportation and emergency management. In this paper we investigate how to define adaptivity for complex Pervasive Grid applications by providing multiple versions of application parallel modules. The versions are defined by exploiting different sequential algorithms and parallelization techniques. We introduce per- formance analysis tools for versions, which allow us to define specific selection policies of the best version to be executed, depending on the context. We show how each version is best suited to be executed on two application scenarios, also by means of experiments. To synthesize the contributions of this paper we introduce the ASSISTANT programming model, for adaptive Pervasive Grid applications.
978-076953908-9
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11568/130733
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