Intelligent energy efficient vehicle automation system with sensible edge processing protocol in Internet of Vehicles using hybrid optimization strategy

For improving productivity sectors, the Internet of Vehicles (IoV) is designed based on the interchange between the Internet of Things and automated vehicle schemes in smart cities. The IoV utilizes the road side unit and closely available models to carry out several needs of vehicles. Due to the rapid development of vehicle count and traffic delivery, creative download plans should be implemented to enhance the quality of customer service. The lack of proper intelligence leads to making offloading and discharging more complicated. Hence, this paper focuses on developing a novel energy-efficient framework in sensible edge processing for IoV devices. This model helps to efficiently perform vehicle activity discharging under the determined time with the minimum energy consumption. The sensible edge processing model is incorporated with both undirected and similar activity discharging protocol, where it has included the information regarding the number of duties per unit time and determined time for importing the information. Here, the hybrid optimization strategy named hybrid sail fish tunicate swarm optimization is utilized for optimizing the route from the vehicle to the roadside unit and the interaction stream to achieve the objective function of reducing the total transmission delay and also minimizing the energy consumed during discharge. The experimental results show that the suggested model enhances the performance rate with less transmission delay and less energy consumption for vehicle automation systems.