Research on the Intelligent Scheduling and Allocation Method for Big Data Computing Resources Based on Computing Power Networks

Today's fast development of big data technology poses a significant challenge to efficient scheduling and allocation of computing resources in computer science. Within the newest network architecture, computing power networks are in charge of scheduling resources in the most dynamic and efficient way while processing big data. The research presented here concentrates on deploying intelligent scheduling and allocation algorithm for computing power networks to achieve big data processing. Initially, the article examines the key challenges and problems that exist in big data resource scheduling, subsequently, a model of intelligent scheduling based on computing networks is introduced. This model uses cutting-edge smart scheduling algorithms to fulfill the tasks of the real-time demand for big data and network conditions, thereby realizing the goals of computing efficiency and resource utilization. It is proven by the experimental results that the proposed method can greatly enhance the resource scheduling effectiveness and performance optimization and it wins over traditional approaches in tackling the complexity and volatility of big data task. In the end, the study recapitulates the most important results and a few directions for future research are suggested.