Adaptivity in Risk and Emergency Management Applications on Pervasive Grids

Pervasive Grid computing platforms are composed of a variety of xed 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 environmental 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 de ne adaptivity for complex Pervasive Grid applications by providing multiple versions of application parallel modules. The versions are de ned by exploiting different sequential algorithms and parallelization techniques. We introduce performance analysis tools for versions, which allow us to de ne 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.