|نویسندگان||Mottahedi Mehrnaz, Sam Jabbehdari and Sepideh Adabi|
Study of Vehicular Ad-hoc Networks (VANETs) is among challenges facing researchers today. Nodes in such networks have a relatively high speed, while there is a great shortage of the time needed for data transmission between them as a result of node speed difference as well as persistent changing of the network. Consequently, routing algorithms and modes of access to the conductor is considered as a serious challenge in such networks. In this context, researchers have introduced various protocols, including cluster-oriented methods to overcome such challenges. In cluster-oriented methods, it is of vital importance to a sustainable cluster with due regards to the high speed and density of nodes. The proposed method is called Intelligent Based Clustering Algorithm in VANET (IBCAV), The present project seeks to improve routing algorithms in VANETs by employing inter-layered methods, awareness of the existing traffic flow as well as combination of various factors on the basis of a smart method based on artificial neural network. Here cluster size, speed and density of nodes are the factors which have taken into account. Finally, our simulated results show that the IBCAV outperforms better than AODV, DSR and epidemic routing in terms of packet delivery ratio, end-to-end delays and throughput.
کلید واژه ها: VANET,Routing,Clustering,artificial neural network