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Adaptive Solutions for Data Sharing in Vehicular Networks

Adaptive Solutions for Data Sharing in Vehicular Networks

Good PhD Thesis on Adaptive Solutions for Data Sharing in Vehicular Networks

Research Area:  Vehicular Ad Hoc Networks


   In the context of Intelligent Transportation Systems - ITS, vehicles may have a lot of sensors (e.g. cameras, lidars, radars) and applications (collision avoidance, traffic monitoring, etc.) generating data. They represent then an important source of information. Local applications can significantly increase their effectiveness by sharing such an information within the network. Data accuracy, confidence and pertinence can be verified when receiving data from other nodes.
    In this thesis we address the problem of data sharing in dynamic networks by relying in so-called horizons of pertinence. A horizon is defined as an area within which an information is expected to be received. We start focusing on data sharing within direct neighbors (at 1-hop of distance). Then we propose a solution to construct a map of neighbors, centered in the ego-node, within a horizon of n-hops.
    For this purpose a unique frame is forwarded from node to node. Its payload is locally updated so that it contains the most relevant data items according to some criteria (e.g. urgency, relevance). Such a strategy defines thus a data-centered horizon. We validate our proposals by means of realistic network emulations. From all our studies and achieved results we can state that our approach brings interesting insights for data sharing in dynamic networks like VANETs.

Name of the Researcher:  Hermes Pimenta de Moraes Junior

Name of the Supervisor(s):  Bertrand Ducourthial

Year of Completion:  2018

University:  UTC University

Thesis Link:   Home Page Url