GRASSI Giulio

PhD graduated
Team : NPA
Departure date : 12/31/2017
Supervision : Giovanni PAU

Connected cars: a networking challenge and a computing resource for Smart cities

Cities are getting "smarter and smarter", with a plethora of IoT devices and sensors deployed all over the urban areas. Among those intelligent objects, an important role may be played by cars. Moderns vehicles are (or will be) indeed equipped with multiple network interfaces, they have (or will have) computational capabilities and devices able to sense the environment. To make the connected-car concept possible and deal with the diversity of network interfaces and vehicles' mobility, however, a shift in the Internet model, to a more content based paradigm, is needed. This thesis thus analyzes the benefits and the challenges of the Information Centric Networking (ICN) paradigm, in particular of Named Data Networking (NDN), in the VANET domain, presenting the first implementation running on real cars of NDN for VANET (V-NDN). It then proposes Navigo, a NDN based forwarding mechanism for content retrieval over V2V and V2I communication. Afterwards, the last challenge in the connected-car concept is addressed, the data-provider-mobility problem, proposing an NDN-based solution, dubbed MAP-Me. The vehicle's role in the smart cities however doesn't stop at the connectivity component. Cars, with their new computation capabilities, are the perfect candidates to play a role in the recently proposed Fog Computing architecture. Such an architecture moves computational tasks typical of the cloud to the edge, closer to where the data is produced. As proof of concept, this thesis presents ParkMaster, a fully deployed system that combines machine learning techniques, the edge and the cloud to sense the environment and tackle the parking availability problem.ities are getting "smarter and smarter", with a plethora of IoT devices and sensors deployed all over the urban areas. Among those intelligent objects, an important role may be played by cars. Moderns vehicles are (or will be) indeed equipped with multiple network interfaces, they have (or will have) computational capabilities and devices able to sense the environment. To make the connected-car concept possible and deal with the diversity of network interfaces and vehicles' mobility, however, a shift in the Internet model, to a more content based paradigm, is needed. This thesis thus analyzes the benefits and the challenges of the Information Centric Networking (ICN) paradigm, in particular of Named Data Networking (NDN), in the VANET domain, presenting the first implementation running on real cars of NDN for VANET (V-NDN). It then proposes Navigo, a NDN based forwarding mechanism for content retrieval over V2V and V2I communication. Afterwards, the last challenge in the connected-car concept is addressed, the data-provider-mobility problem, proposing an NDN-based solution, dubbed MAP-Me. The vehicle's role in the smart cities however doesn't stop at the connectivity component. Cars, with their new computation capabilities, are the perfect candidates to play a role in the recently proposed Fog Computing architecture.
Such an architecture moves computational tasks typical of the cloud to the edge, closer to where the data is produced. As proof of concept, this thesis presents ParkMaster, a fully deployed system that combines machine learning techniques, the edge and the cloud to sense the environment and tackle the parking availability problem.
Defence : 10/31/2017 - 14h00 - Site Jussieu 25-26/105
Jury members :
Alexander Afanasyev, Assistant professor, Florida International University [Rapporteur]
Mario Gerla, Professor, University of California, Los Angeles [Rapporteur]
Serge Fdida Professor, UPMC Sorbonne Universités
Giovanna Carofiglio Distinguished engineers, Cisco Paris
Jérôme Härri Assistant professor, Eurecom
Giovanni Pau Professor, UPMC Sorbonne Universités

2013-2018 Publications

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