Abstract:

The current data center equipment energy consumption and data access laws are analyzed. Based on the research result, the cloud data model is created, and the energysaving technologies are researched based on cloud task scheduling and data deployment, then a novel dynamic data aggregation algorithm is proposed for green cloud data centers. The data aggregation algorithm is divided into two levels: data aggregation and node aggregation. The main idea of this algorithm is that, with the consideration of quality of service, the data can be aggregated reasonably according to the data access laws in order to realize the orderly aggregation and re-deployment of data and nodes deployed randomly before. The computing and storage nodes can take turns running, resulting in the accurate, highlytargeted temperature control of cooling equipment cooperating with servers. The algorithm achieves the goals of full use of resources, meeting the needs of users and reducing the overall system energy consumption. The results of the simulation experiments and the analysis of performance show that the proposed algorithm can maintain the quality of service for cloud data centers, improve the equipment reliability and achieve the “green” energy-saving goal.