Reference : Connectivity Analysis of Wireless Sensor Networks Deployments in Smart Cities
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/22735
Connectivity Analysis of Wireless Sensor Networks Deployments in Smart Cities
English
Faye, Sébastien mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Chaudet, Claude mailto [Institut Mines-Telecom, Telecom ParisTech > INFRES]
24-Nov-2015
Proceedings of the 22nd IEEE Symposium on Communications and Vehicular Technology in the Benelux (SCVT 2015)
Yes
International
22nd IEEE Symposium on Communications and Vehicular Technology in the Benelux (SCVT 2015)
November 24, 2015
Luxembourg
Luxembourg
[en] Smart Cities ; Wireless Sensor Networks ; Network Topology
[en] Recent advances in the field of intelligent transportation systems have focused on the use of wireless networks to link vehicles and road infrastructure. Applications that might result from such networks range from the adaptive management of traffic lights to the detection of traffic jams and accidents. Whatever the case may be, it seems important to explore the possibilities and limitations of such networks, which the literature often portrays in a somewhat idealistic way (e.g. no packet loss, fully connected sensors, etc.). In this paper, we study the deployment of wireless sensor networks at intersections in some of the world's major cities and characterize their topologies. Using a propagation model that corresponds to a 2.4GHz IEEE 802.15.4 network interface, we focus our study on the global connectivity of graphs resulting from different networks. By deploying this type of network over 52 city and region maps extracted from OpenStreetMap, we show that cities can reasonably be classified into three network structure categories of low connectivity (i.e. a high number of connected components) and that it should be feasible to improve the networks by adding sensors. All the tools and the complete dataset are freely available online.
Researchers ; Professionals ; Students ; General public
http://hdl.handle.net/10993/22735
10.1109/SCVT.2015.7374221

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