Research on task offloading minimizing energy consumption based on edge computing in Internet of Vehicles
Zhaojuan Deng, Xiaofang Deng · 2025
With the rapid advancement of intelligent transportation systems, vehicle users are placing increasing emphasis on low latency and high-quality service for computing tasks. As a pivotal technological paradigm, Mobile Edge Computing (MEC) offers low-latency response capabilities and robust service guarantees for the Internet of Vehicles (IoV). Nevertheless, when MEC is integrated into IoV, task offloading to MEC servers inevitably incurs transmission energy consumption. To solve this problem, under the framework of Internet of Vehicles and MEC, the idle computing resources are fully mobilized, and the task offloading model is constructed with the goal of minimizing energy consumption. The improved genetic algorithm is used to solve the optimal offloading power and offloading parameters. Simulation results demonstrate that the proposed scheme can substantially reduce the energy consumption associated with task processing at vehicle terminals.