This invention discloses an
intelligent computing center performance evaluation and optimization
management system, belonging to the field of
intelligent computing center management technology. The
system includes a
data acquisition module, a data preprocessing module, a performance evaluation module, an optimization decision-making module, an
execution control module, and a data storage module. The
data acquisition module uses IoT sensors and
edge computing nodes to collect real-time operating data from various devices and transmits it encrypted. The data preprocessing module uses the Spark Streaming framework to clean and denoise the data. The performance evaluation module integrates a CNN-LSTM
hybrid network and the
Analytic Hierarchy Process (AHP) to generate a comprehensive performance
score through a formula. The optimization decision-making module uses
reinforcement learning and other algorithms, combined with a digital twin engine and
energy consumption prediction formulas, to generate the optimal
resource scheduling scheme. This
system achieves comprehensive
data acquisition, accurate performance evaluation, scientific optimization decision-making, and efficient
execution control for
intelligent computing centers, improving operating efficiency and reducing
energy consumption, and has high practical value.