## 2 Related Work
### Routing Protocols in VANETs  
The dynamism, rapid mobility, and variable node densities that characterize the VANET environment hamper the collection and sharing of data, especially when high latencies are not tolerated [24]. Protocols based on geographic routing and clustering are currently seen as the most efficient choices, due to their efficient use of control messages. Geographic protocols use the nodes' positions to make routing decisions. Among the best known, IGRP [34] focused on selecting sequence of intersections for the packets to reach fixed gateway nodes (GWs). The GWs maintain an up-to-date view of the network topology. Therefore, every time a vehicle moves away from its current position a distance greater than its transmission range, it sends the nearby GWs a report with its updated location. This information allows the calculation of a set of routes to maximize the QoS parameters. An alternative approach was presented in [35], based on a data dissemination scheme to perform intelligent forwarding, by selecting the next hop according to the stability of the connection and the link durations.  
In clustering-based protocols, the idea is to introduce a hierarchy to handle manageable amounts of control messages, by arranging the moving vehicles in groups (typically, on the grounds of geographical proximity and relative movement) and designating one of them as the cluster head to channel the communications with the neighboring groups. An interesting analysis of approaches to form clusters was presented in [36], while the work in [37] enumerated parameters relevant for the selection of the cluster heads. New combinations of approaches for both tasks keep appearing, achieving significant performance improvements in simulation experiments [38]. As the routing protocol between cluster heads, it is still common to find variations of classical algorithms--such as AODV or OLSR--to use the most reliable routes from source to destination. For example, in [39] the traditional system for the detection of route breakages (based on the loss of HELLO messages) was replaced by a forecasting indicator that used information about errors in the decoding of OFDM packets. The authors of [40], in turn, developed a framework that analyzes network resources in order to adjust the relationship between topology changes and QoS needs, aiming to decrease the load on the VANET and thereby improve scalability. Other authors have attained improvements by incorporating machine learning techniques that allow the prediction of vehicle mobility [41].  
Finally, there are dedicated protocols running on the same idea of a layer of virtual nodes that supports the proposal in this paper, such as VNAODV+ [42] and VNIBR [43]. On the one hand, VNAODV+ maintains the reactive essence of AODV, including route discovery, packet types, and the configuration of most parameters. The main difference has to do with the changes required to send data through virtual nodes, starting from the fact that routing entities are not identified by IP addresses but by region. On the other hand, VNIBR is an intersection-based geographical protocol in which all routing decisions are made at road intersections, where the virtual nodes maintain routing tables as persistent state information.