Green-Edge Computing-Based IoV Dynamic Task Collaborative Strategy

With the rapid development of Internet of Vehicles (IoV), the demand for data processing and computing power is increasing exponentially, creating significant challenges to edge computing, with the most prominent being resource constraints and the urgent need for green computing. To tackle the challenges mentioned above, this article proposes a dynamic task collaborative strategy based on green edge computing for IoV. Specifically, the strategy encompasses a novel multi-dimensional dynamic offloading decision system that facilitates collaborative offloading between edge servers and vehicles on the road, thereby overcoming resource constraints. Additionally, we have integrated energy harvesting technology into edge servers and constructed a new energy harvesting model by taking into account both environmental and device factors, enabling more accurate predictions of the harvesting energy. Meanwhile, the article focuses on the dynamic offloading scenario during the movement of vehicles, applying latency and energy consumption as evaluation indicators to minimize system cost. To solve above optimization problem, an improved hippopotamus algorithm is proposed. Finally, simulation results demonstrate the effectiveness of proposed algorithm and strategy in enhancing the performance and sustainability of IoV.