## 1 Introduction
The solution methods rely on specific concepts such as the Internet of Things (IoT), whose paradigm is shown in Figure 1. IoT refers to any technology that allows the integration of different objects to the communications environment in such a way that the physic world could be accessed and managed through software. The main components involves traditional communication technologies (GSM, LTE, Wimax, _etc._), and sensors and actuators in the target objects. The concepts of vehicle-to-vehicle (V2V) communication and vehicle-to-infrastructure (V2I) communication have been introduced as subsets of IoT. V2V communication, shown in Figure 2a, allows two vehicles to interact directly without relying on a fixed communication infrastructure, while V2I communication, shown in Figure 2b, allows a vehicle to communicate with the elements of the road infrastructure such as traffic-light controllers, intelligent signal  
Figure 1: Internet of Things paradigm. In the specific case of vehicle routing, traditional methods are based in static variables or the information derived from the road context is well known or calculated before the route is assigned to vehicles. This information usually does not change over time, for example, [PERSON]'s algorithm [7] based-approaches that focus in the minimal distance [8], or modified versions of Dijkstra that change the cost function to another parameters, _i.e._, trip time, but assume they can be settled before the calculation of routes. In the case of congestion, this variable is not usually part of the optimization function in most of proposals, that means, developed methods are congestion aware but not congestion oriented. Moreover, when congestion must be taken into account, it is derived from other variables as expected time or velocity, but as mentioned before, those works can establish precalculated values to eliminate the dynamism in global congestion state ([9, 10, 11]). The reason of this is the high cost of maintaining and processing the changing congestion state in a way it is relevant for the decisions made. That's why V2I and V2V systems are essential for addressing problems that involve high dynamic parameters. They allow the integration and collaboration of a high number of devices making the task of collecting and processing information of the context less complex. The work in this paper was to develop a method in which condition to evaluate a route involves the definition of congestion in the path followed by the vehicle. Also, this method will be supported by a communication mechanism based on V2I or V2V communication allowing to address the problem of getting the most relevant global state of congestion in a totally dynamic environment. In addition, we evaluate the proposed method in terms of how efficient is the usage of available streets and propose an optimization model over the load balancing of the streets. Figure 2: Representation of V2V and V2I technologies. (**a**) V2V communication; (**b**) V2I communication. The rest of this paper is organized as follows: in Section 2 related work is discussed. In Section 3 the optimization model for load balancing of the use of capacity in each street is proposed. In Section 4 proposed mechanism of congestion-based is described as the supporting infrastructure. In Section 5 the simulation description, validation scenarios and results are presented. Finally in Section 6 we present the conclusions and future work.