Towards a flexible data stream analytics platform based on the GCM autonomous software component technology

Abstract : Big data stream analytics platforms not only need to support performance-dictated elasticity benefiting for instance from Cloud environments. They should also support analytics that can evolve dynamically from the application viewpoint, given data nature can change so the necessary treatments on them. The benefit is that this can avoid to undeploy the current analytics, modify it off-line, redeploy the new version, and resume the analysis, missing data that arrived in the meantime. We also believe that such evolution should better be driven by autonomic behaviors whenever possible. We argue that a software component based technology, as the one we have developed so far, GCM/ProActive, can be a good fit to these needs. Using it, we present our solution, still under development, named GCM-streaming, which to our knowledge seems to be quite original.
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Communication dans un congrès
The 2016 International Conference on High Performance Computing & Simulation (HPCS 2016), Jul 2016, Innsbruck, Austria. HPCS 2016, workshop on Autonomic HPC, <http://hpcs2016.cisedu.info/home>


https://hal.archives-ouvertes.fr/hal-01323445
Contributeur : Francoise Baude <>
Soumis le : mercredi 20 juillet 2016 - 12:37:10
Dernière modification le : mardi 26 juillet 2016 - 01:04:27

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Distributed under a Creative Commons Paternité 4.0 International License

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  • HAL Id : hal-01323445, version 1

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Françoise Baude, Léa El Beze, Miguel Oliva. Towards a flexible data stream analytics platform based on the GCM autonomous software component technology. The 2016 International Conference on High Performance Computing & Simulation (HPCS 2016), Jul 2016, Innsbruck, Austria. HPCS 2016, workshop on Autonomic HPC, <http://hpcs2016.cisedu.info/home>. <hal-01323445>

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