Creative achievement, Journal paper

Characterizing the Topology of an Urban Wireless Sensor Network for Road Traffic Management

In a near future, wireless networks will be one of the key technologies for road traffic management in smart cities. Vehicles and dedicated roadside units should be interconnected through wireless technologies such as IEEE 802.11p (WAVE). Traffic light and road signs may also take their place in this architecture, forming a large-scale network of small devices that report measurements, take orders from a control center, and are able to take decisions autonomously based on their local perception. Such a network shares many similarities with classical wireless sensor and actuator networks, starting with its distributed organization and with the role of the control center. However, its topology, and subsequently the appropriate selection of protocols and algorithms, will be strongly influenced by each city’s characteristics. In this article, we characterize and discuss probable topologies of these networks. The aim of this work is to provide network models that can be used to evaluate protocols and algorithms using realistic scenarios in place of generic random graphs. We deploy such networks over 52 city maps extracted from OpenStreetMap and characterize the resulting graphs, with a particular focus on connectivity aspects (degree distribution and connected components). The tools, the complete datasets, OMNeT++ network models are available freely online.

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  • S. Faye and C. Chaudet, “Characterizing the Topology of an Urban Wireless Sensor Network for Road Traffic Management,” IEEE Transactions on Vehicular Technology, vol. 65, iss. 7, pp. 5720-5725, 2016. | [PDF] Paper[DOI] LinkBibtex citation
    Author = {Faye, S{\'e}bastien and Chaudet, Claude},
    Doi = {10.1109/TVT.2015.2465811},
    Journal = {IEEE Transactions on Vehicular Technology},
    Month = jul,
    Number = 7,
    Pages = {5720--5725},
    Pdf = {},
    Title = {Characterizing the Topology of an Urban Wireless Sensor Network for Road Traffic Management},
    Volume = 65,
    Year = 2016,
    Bdsk-Url-1 = {}}