Vehicle Networking Edge Computing Offloading Problem Based on Whale Optimization Algorithm

The rapid development of the Internet of Vehicles has put forward higher requirements for task offloading. Users focus on the service quality of vehicular applications, while edge server operators focus on reducing energy consumption and ensuring load balancing. In addition, there is the fierce competition in terms of edge servers due to offloading simultaneously, global optimization has become a research focus. In response to these requirements, this paper models the task offloading as a multi-user multi-objective optimization problem, and proposes an algorithm that integrates NSGA-II and the whale optimization algorithm and showcasing superior performance in terms of delay, energy efficiency, and resource utilization outperforms existing solutions. Through comparing with other offloading schemes, the results show that the proposed algorithms can significantly reduce task offloading delay and system energy consumption while maintaining load balance.