InfoRank: Information-Centric Autonomous Identification of Popular Smart Vehicles

Junaid Ahmed Khan (1, 2) , Yacine Ghamri-Doudane (1) , Dmitri Botvich (3)

1 L3I - Laboratoire Informatique, Image et Interaction - EA 2118
2 LIGM - Laboratoire d'Informatique Gaspard-Monge
3 Waterford Institute of Technology

Modern cars are transforming towards autonomous cars capable to make intelligent decisions to facilitate our travel comfort and safety. Such " Smart Vehicles " are equipped with various sensor platforms and cameras to collect, store and share tremendous amount of heterogeneous data from urban streets. This paper addresses the efficient collection and distribution of such massive data by allowing a popular Smart Vehicle to autonomously decide its user relevant importance in the vehicular network without relying on the infrastructure network. Therefore , we propose an Information-Centric algorithm, " InfoRank " for a vehicle to rank different location-dependent information associated to it. It then uses the information importance to analytically find its influence in the network. InfoRank is the first step towards identifying the best information hubs to be used in the network for the efficient collection, storage and distribution of urban sensory information. Results from scalable simulations using realistic vehicular mobility traces show that InfoRank is an efficient ranking algorithm to find top information facilitator vehicles in comparison to other ranking metrics in the literature.

Mots clés: Information-Centric Vehicular Networking; Urban Sensing and monitoring

Domaines: Informatique [cs]

Junaid Ahmed Khan, Yacine Ghamri-Doudane, Dmitri Botvich. InfoRank: Information-Centric Autonomous Identification of Popular Smart Vehicles. IEEE VTC Fall 2015, Sep 2015, Boston, MA, United States. pp.6, ⟨10.1109/VTCFall.2015.7390985⟩. ⟨hal-01283729⟩