Intelligent Humming Bird Optimization Based Distance Aware Routing Scheme for Vehicular Networks

In recent times, vehicular ad hoc network (VANET) has been significantly considered by several service providers from urban locations. Such a network could not only prevent accidents and enhance road safety but among them offer a means of entertainment to passengers. But, based on the present analysis, effective routing is until remained a big open problem for the VANETs. The vehicle's limited broadcast range reasons the route for participating from data broadcast in the source S to destination D can vanish seldom. So, the stable route from source to destination requires for delivering data packets at planned destination. This study designs an Intelligent Artificial Humming Bird Optimization based Distance Aware Routing (IAHBO-DAR) scheme for VANET. The presented IAHBO-DAR model mainly considered the distance metric for route selection process. The IAHBO-DAR model is based on the integration of standard AHBO algorithm with dynamic oppositional based learning (DOBL) concept. In addition, the IAHBO-DAR model computes a fitness function with three variables like node degree (ND), residual energy (RE), and distance. A wide range of simulations have been conducted to exhibit the enhanced routing performance of the IAHBO-DAR approach. The experimental value demonstrates the betterment of the IAHBO-DAR algorithm compared to recent approaches.