## 2 Related Works  
Historically, real-time traffic monitoring and congestion-detection systems relied on police reports or dedicated road sensors (e.g., buried inductive loops, active infrared sensors, cameras and radars). In recent years, the widespread diffusion of cellular communications has enabled the design of traffic estimation techniques based on data provided by cellular operators. Typically, cellular networks are used as a source of anonymous geo-referenced raw data, stored and processed in a remote data center in order to extract information on the traffic intensity. Relevant examples of this approach are: (i) the TrafficSense system developed by Cellint Traffic Solutions Ltd [12]; and (ii) the Localizing and Handling Network Event Systems (LockHNESs) platform developed by Telecom Italia, which allows a real-time evaluation of urban dynamics based on the anonymous monitoring of mobile cellular networks [13]. An alternative approach consists in using the smartphones themselves to build distributed location-based services (LBSs), through suitable distributed algorithms and overlays. Distributed LBSs are a clear example of geo-collaboration services, where active users can efficiently discover and disseminate information about existing services (such as a video stream from a webcam, storage volunteers and others), geo-referenced objects and information (e.g., positions of gasoline stations, accidents, bad surface conditions, traffic jams). These approaches, combined with mobile phone-based nodes, allow building distributed applications to harvest efficient traffic information, travel time and auxiliary data in the regions of interest. [PERSON] _et al._, with Peers on Wheels [14] and, more recently, with PeerTIS [15], proposed P2P (Peer-to-Peer) architectures, where participating cars are peers organized in a Distributed Hash Table (DHT), to receive and distribute useful information to improve the vehicle travel time using dynamic route guidance. A different P2P approach, called _Distributed Geographic Table_ (DGT), was proposed in [16] and applied to a real smartphone-based Traffic Information System (TIS) scenario in [17]. The DGT is a structured overlay scheme, where each participant can efficiently retrieve node or resource information (data or services) located near any chosen geographic position. In such a system, the responsibility for maintaining information about the positions of active peers is distributed among nodes, for which a change in the set of participants causes a minimal amount of disruption. The overlay is different from other P2P-based localization systems (DHT and tree-based overlays), where geographic information is routed, stored and retrieved among nodes, which are organized according to a structured overlay scheme. The DGT idea is to build up the overlay directly, taking into account the geographic positions of the nodes and any other information required to build a network, where overlay neighbors are also geographic neighbors and no additional messages are needed to obtain the closest neighborhood of a peer. Hybrid vehicular networks, relying also on cellular connectivity, provide a good solution to overcome the coverage limitations of pure-VANET solutions when the vehicle spatial density is low, thus allowing one to reach an increased number of potentially isolated vehicles [4]. Open issues are (i) the data exchange cost over the cellular infrastructure and (ii) the latency of data delivery, which is higher than the pure-VANET approach. Therefore, cellular network-based distributed architectures are not suitable for short-range safety-driving applications, but could be efficiently applied in scenarios where (i) latency is not an issue and (ii) the distance from the event or generic geo-localized information is sufficient to guarantee proper data dissemination. Regardless of the origin of the information, the issue of real-time dissemination of this information to the interested vehicles is still an open problem.