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A Novel Framework for QoS based Robust Routing Algorithms for VANET using GRBF-MLP and CH-BFA
Lakshmana Kumar. R, Sivaparthipan CB, BalaAnand Muthu
Sufficient communication is established between vehicles by the Vehicular Ad-Hoc Network (VANET). Recently, one of the most demanding and crucial processes is enhancing the Quality of Service (QoS) in VANET. Thus, in the present works, several Routing Protocols (RP) are developed. Nevertheless, it still fails to provide the best packet transmission. Thus, a novel framework is proposed for QoS-based Robust Routing Algorithms for VANET. It has two phases. The packet attributes are extracted and numeralized initially in the 1st phase. The numeralized attributes are inputted into the Generalized Radial Basis Function-based Multi-Layer Perceptron (GRBF-MLP) network, which classifies the responsible nodes. The test packets are transmitted in the 2nd phase. By employing the Time stamp- based Divide and Conquer scrypt hashing (TDC-scrypt) method, the flooding packets are filtered. Next, by deploying the Gini Coefficient and Hamming distance-based K Means clustering (GH-K Means) algorithm, the nodes are clustered. Then, by utilizing Z- the Score Z-score-based Tuna Swarm Optimization Algorithm (ZS-TSOA), the CH is selected; also, by employing Convex Hull-based Bellman Ford Algorithm (CH-BFA), the shortest path is created. The proposed model’s outcomes are analogized to the prevailing techniques, which show the higher efficacy of the developed model.
Keywords: Generalized Radial Basis Function-based Multi-Layer Perceptron (GRBF-MLP) network, Time stamp-based Divide and Conquer scrypt hashing method (TDC-scrypt), Gini Coefficient and Hamming distance-based K Means clustering (GH-K Means) algorithm, Z- Score based Tuna Swarm Optimization Algorithm (ZS-TSOA), Convex Hull-based Bellman Ford Algorithm (CH-BFA)