Predictive Hybrid Routing with Multi Objective Optimization Model for Opportunistic Routing for VANET

Opportunistic network model is one among the prediction-based routing approach for effective transmission of data. In opportunistic network identification of routing path are critical task due to mobility and dynamic nature of network. In microscopic opportunistic routing approach, route prediction is an essential factor for effective communication. In addition to that decision making is also plays an important role in computation of routes. In order to overcome this entire problem we introduced a novel mechanism namely Fuzzy Set Theory with Whale Optimization Algorithm (FST-WOA). The first objective is to develop appropriate machine learning based that incorporates fuzzy set theory for prediction of routes in the network based on the distance, number of hop and energy level of nodes. ALEXNET architectural model is used for route prediction in fuzzy set theory. This fuzzy based ALEXNET model integrated with multi-objective optimization technique called Whale Optimization Algorithm (WOA). For the process of simulation Network Simulator (NS3) is used. The proposed method is tested and compared with the earlier models such as BOR and RLFGRP. The parameters used for the process of performance analysis are, latency calculation, Packet Delivery Ratio and routing overhead.