Some novel investigation on enhancing network connectivity for efficient communication in vehicular adhoc network vanet

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Vehicular Ad hoc Network (VANET) is a special kind of self-organizing wireless mobile ad hoc network. It is formed by a set of moving vehicles equipped with On-Board Unit (OBU) and fixed infrastructures called as Road Side Unit (RSU). The communication in VANET takes place either by using Vehicle to Vehicle communication (V2V) or Vehicle to Infrastructure communication (V2I) or both. Moreover, the unique features of VANET that differ from MANET are rapid mobility of vehicles, limited degree of freedom in moving patterns, lane changing behaviors, uneven distribution of vehicles, dynamic topology, frequent network disconnection, and lack of centralized control. These features are the significant challenges in designing efficient connectivity protocols. Further, coverage and connectivity among nodes are the most significant characteristics for providing seamless communication in VANET. So, it is essential to develop sufficient coverage and connectivity schemes to enhance the connectivity among the nodes to afford reliable communication. There is a high demand for novel connectivity model architecture to be developed in VANET to enhance the connectivity among vehicles in low density highway environment. The main objective of this thesis is to design and develop connectivity models for VANET highway scenarios. The connectivity of the network can be enhanced by implementing the following studies. The first study enforces seamless connectivity among vehicles through designing a suitable mobility and lane changing model for the highway environment. The proposed protocol High Speed Mobility and Lane Changing model (HSMLC) reveals the suitable mobility and lane changing approaches. First, the high speed mobility model is designed based on Adaptive Cruise Control algorithm (ACC). Next, lane changing models are designed using a Recurrent Neural Network (RNN). Finally, the connectivity probability of V2V communication is analyzed using HSMLC newline

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