An Improved Multi-objective Optimization Framework with a Hybrid Model for Vehicular Adhoc Network Routing Services

Abstract

A vehicular ad hoc network (VANET) includes groups of stationary or moving vehicles linked by a wireless network. The significant usage of VANET is to offer comfort and safety to drivers in road environments. VANET provides a communication framework that aids in minimizing accidents. Also, sharing data in VANET is time-sensitive and necessitates vigorous and quick network link formation. However, appropriate routing is critical to avoid the streaming issues that occur in VANET applications. This research area is of great concern to the researchers, and this work intends to propose a new Cluster-based VANET routing model with steps like (a) optimal cluster head selection (CHS) and (b) appropriate gateway selection for data transmission. Here, the optimal CHS takes place considering the Packet delivery ratio (PDR), mean routing load, end-to-end (e2e) Delay, Throughput, and packet overhead. This paper introduced a new Customized hunger’s foraging honey badger with a Dynamic multi-objective non-sorted genetic algorithm (CHFHB-DMNSGA). Also, the gateway selection is done under two objectives: Vehicular gateway mobility and receiver signal strength, respectively. Finally, the paper presented a comparative assessment to validate the effectiveness of the adopted algorithm CHFHB-DMNSGA over the other algorithms like R-NSGA-II, NSGA-III, NSGA-II, HBA, HGS, ABC, FF, CSO, ACO, LA, MHB-GA, GA-FF, and HFCHBO.