Task scheduling strategy for cloud-fog computing system of IoV based on improved quantum genetics and QoS awareness method

An improved quantum genetic and QoS-aware scheduling strategy was proposed to address concurrent congestion, QoS diversity, and complex resource allocation in IoV cloud-fog computing systems. Using quantum encoding and rotation-based optimization, along with QoS balancing parameters and load balancing penalties, the proposed strategy improved makespan, energy efficiency, and scheduling flexibility. Simulation results show that the proposed strategy is up to 69.0% reduction in makespan and strong performance across multiple metrics, supporting practical applicability.