Big data analytics are being applied to a wide range of applications domains, including those in charge of controlling critical real-time systems, challenging the need not only to efficiently processing extreme amounts of complex data, but also processing it in real-time. CLASS aims to develop a novel software architecture framework to help big data developers to efficiently distributing data analytics workloads along the compute continuum (from edge to cloud) in a complete and transparent way, while providing sound real-time guarantees. In particular, the CLASS framework will be able to gather the information from all the smart edges, as smart cameras and autonomous vehicles, in order to build the knowledge of the city. The city will then forward the useful information to the interested autonomous cars in real time, in order to immediately improve the navigability of the cars and with the long term goal to reduce both accidents and pollution. The capabilities of the CLASS framework are applied to a real smart-city use case in the City of Modena.

1. Micaela Verucchi
micaela.verucchi@unimore.it
Modena, 16.05.2019
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2. : Edge and Cloud Computation: a Highly
Distributed Software for Big Data Analytics
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3. : Edge and Cloud Computation: a Highly
Distributed Software for Big Data Analytics
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4. : Edge and Cloud Computation: a Highly
Distributed Software for Big Data Analytics
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Smart citySelf-driving cars Real Time Fog computing

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Goals: short term

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Goals: long term

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The infrastructure
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The infrastructure
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Our self-driving car prototype

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The flow
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The flow
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The flow
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The flow
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The flow
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The flow
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<10 ms

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The flow
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<16 ms

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The flow
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<100 ms

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The flow
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DEMO May the 17th

20. Thank you for your attention
Questions?
Micaela Verucchi - micaela.verucchi@unimore.it