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As the scale of cloud computing expands, its impact on energy and the environment is becoming more and more prominent. According to statistics, data centers’ energy consumption has accounted for 50% of operating costs of the data centers. The rising energy consumption not only needs energy in large quantity but also imposes heavy pressure on the environment. The high energy consumption of cloud data center has become an issue, people pay close attention to, in the information technology field. It is also a problem to be solved urgently. At present, high energy consumption is caused by two reasons. First, a resource scheduling mechanism with the priority of completion time causes low server use ratio, and it is a pervasive phenomenon that small tasks take high consumption. Second, the current refrigerating system of the data center is based on peak value strategy, which causes excessive cooling supply, increases operation cost, and leads to huge waste of energy. In this paper, considering the reason of high energy consumption of the data center, a new framework of green cloud data center is put forward. Using the techniques relevant to artificial intelligence, we put forward a scheduling control engine and an intelligent refrigerating engine aiming at reduction of energy consumption. In addition, we build a green cloud data center platform, realize the scheduling control engine, and verify the feasibility of the framework. It indicates that the framework can realize a cloud platform with low power consumption and a high-energy-efficient data center operation.
Yang et al. (Thu,) studied this question.