Routing Optimization in Vehicular Social Networks Using Firefly Algorithm

Vehicular communications have been considered to be an enabler for numerous vehicle safety and information applications.Vehicle Social Networks (VSNs) are a type of ad-hoc networks which allows wireless communication between two adjacent vehicles. Routing and communicating with adjacent nodes are one of the problems in VSNs. A literature review indicated that the time limit to transmit data and route is a problem due to the geographical distance and speed of the vehicles. The present paper aims to provide an innovative near-optimal solution with minimal delay for the routing problem in these networks, using the optimization algorithm of re y applicable in dynamic and geographi- cally extensive environments. Vehicles and their movements are considered to be re ies and their absorption, respectively. The two factors of mean distance and the possibility of two vehicles reaching each other were examined for car absorption and routing. In addition, the number of vehicles in each area, measured by the different density of vehicles in both urban and suburban areas, is another directly effective factor in the routing accuracy. Finally, the proposed method is simulated in the 5G networks and the results indicated the improvement of the proposed method compared with the dynamic group division algorithm in terms of mean car routing distance, urban, and suburban area separation, light changes, light absorption coeffcient variations, random number between zero and one changes, and random initial vehicle mobility changes up to 14.68, 13.63, 2.65, 20.08, 18.39, 17.57, and 18.45, respectively.