Multi-Constraint Multicast Routing for VANET using Hybridized Ant Colony with Artificial Bee Colony Optimization Algorithm

Vehicular ad hoc network (VANET) is considered as the most significant dimension for implementing Intelligent Transportation Systems (ITS) as it permits inter-vehicular communication through fixed infrastructures named roadside units. The movements of vehicles in VANET depend on the utilized mobility model with multicast routes distributing potential information related to data traffic by means of parallel transmission. Multicast routing reduces the cost incurred in communication as they duplicate a single packet for transmitting it to multiple destinations during multicast routing. The optimal cost of multicasting in VANET can be still reduced by discharging multi-constraints for enforcing maximum efficacy in data dissemination. This distribution of multicast routing information for ensuring reliable data delivery is highly influenced by network scalability. Meta-heuristics algorithms are efficient enough in predicting the near optimal solution for problems with constraints like large problem space with dynamic behaviour. Famous meta-heuristics algorithms like Ant Colony Optimization and Artificial Bee Colony (AC-ABC)is hybridized to have good results that is compared to other algorithms. For solving QoS constraint multicast routing problem in VANET these algorithms are highly suitable due to their efficiency. The exploitation level of the ant colony optimization algorithm makes it adaptable for solving multicasting problem but it suffers from stagnation problem. The exploration rate of the artificial bee colony optimization algorithm is good but poor in exploitation with slow convergence. Thus, these two algorithms can be integrated to extract the benefits of each algorithms for solving the multi-constraint multicast routing in VANET environment.