Data di Pubblicazione:
2019
Abstract:
The Internet of Things is expected to generate an unprecedented number of unbounded data streams that will produce a paradigm shift when it comes to data analytics. We are moving away from performing analytics in a public or private cloud to performing analytics locally at the fog and edge resources. In this paper, we propose a network of tasks utilizing edge, fog, and cloud computing that are designed to support an Analytics Everywhere framework. The aim is to integrate a variety of computational resources and analytical capabilities according to a data life-cycle. We demonstrate the proposed framework using an application in smart transit.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
Internet of Things; Computational Platforms; Machine Learning
Elenco autori:
Renso, Chiara; Carlini, Emanuele
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