Abstract:Abstract: Cloud computing data centers are getting bigger and bigger, the hardware scale is increasing, and there will be a large amount of computing resources and storage resources will appear in the cloud, prompting a large number of 100,000, millions, or even millions. The data center of the server is also available, and the server can also be incrementally expanded and incrementally deployed. The problem of high energy consumption has become increasingly prominent, which seriously restricts the sustainability of the cloud computing data center. This paper proposes a new cloud computing data center scalable server energy-saving optimization strategy-performance optimization strategy, which can reduce energy consumption based on the global perspective, optimize the server selection process, and also promote load balancing between different servers. The simulation results show that the performance optimization strategy proposed in this paper saves 15.23% and 24.33% respectively compared with the DVFS strategy and the non-migration strategy. Based on the migration number, the performance optimization proposed in this paper is based on the migration number. The strategy reduces the number of migrations corresponding to the DVFS strategy by 2,425 times. In summary, the performance optimization strategy proposed in this paper is generally superior to the DVFS strategy and the non-migration strategy.