Research on the Resource Allocation Optimization Model of Automobile Based on Cloud Computing Resource Scheduling Algorithm

This paper proposes a global resource allocation optimization model based on cloud computing, aiming to improve the global resource management efficiency of automobile enterprises through cloud computing resource scheduling algorithm. The system makes full use of the flexibility and scalability of cloud computing, and designs a set of advanced resource scheduling algorithms, which can dynamically adjust the allocation of computing resources according to the changes in demand in different markets and regions around the world, ensuring that resources can be optimally configured at different times and regions. The simulation results show that the model has significantly improved the resource allocation efficiency compared with traditional methods, which not only greatly improves the resource utilization rate, but also effectively reduces the operating costs of enterprises. The cloud computing resource scheduling algorithm shows higher computing efficiency and economic benefits when dealing with complex resource allocation problems. Compared with the traditional static scheduling method, the algorithm proposed in this paper shows its excellent adaptability when dealing with fluctuations in global resource demand, and provides a new technical path and practical basis for the resource allocation optimization of automobile enterprises in the context of globalization.