Efficient deployment of roadside units in vehicular networks using optimization methods

Nowadays, vehicles have become more and more intelligent and equipped with highly sophisticated systems. This allows them to communicate with each other and with the roadside units (RSUs). Furthermore, to ensure efficient data dissemination in vehicular ad hoc networks (VANETs), it is recommended that a Vehicle-to-Infrastructure (V2I) architecture be chosen where RSUs will be installed at intersections. Nevertheless, it is not advisable to place an RSU at each intersection because of their high cost. It is therefore appropriate to reduce the number of RSUs by choosing locations at intersections that maximize the surface covered of the urban area and minimize the area of overlapping zones. Moreover, deploying an optimal number of RSUs in an urban area meeting the above requirements is an NP-hard problem since the number of combinations is very high when the number of intersections is very large. For this purpose, we used metaheuristic approaches. The first approach is represented by the standard version of genetic algorithms (GA-Basic) and its improved version (GA-Improved) while the second approach is based on the standard version of simulated annealing (SA-Basic) and its improved version (SA-Improved). The proposed approaches are evaluated over OMNET++ simulator. The results obtained showed that the GA-Improved approach deploys a reduced number of RSUs (37.5%) while guaranteeing acceptable routing performance compared to the GA-Basic, SA-Basic, and SA-Improved approaches which deploy 46.25%, 65%, and 52.50%, respectively, for the same routing performance.

Automated summary

Modern vehicles are equipped with sophisticated systems for communication through RSUs. Deploying an optimal number of RSUs in urban areas requires the use of metaheuristic approaches such as genetic algorithms and simulated annealing.