A hybrid Algorithms to Improve the Quality of Service in Vehicular Ad-Hoc Networks: A Framework

In recent years, the need to implement effective systems to optimize vehicle traffic congestion problems in cities has increased due to the increase of vehicle nodes in the vehicle communication network. The recent developments in science have shown that much of the previous types focus on designing fuzzy systems of inference systems based on the model of vehicular congestion, which detects and minimizes congestion levels with much focus. However, VANET approaches to congestion management face many problems, including high delivery delays, inefficient use of services, insufficient bandwidth use, overhead connections, etc. In this paper, we propose a new framework to tackle the congestion management problem in VANET. This is achieved using a different algorithm (ABOGA and K-means). This work benefits from and combines each algorithm to produce a stable, high performance network.