Abstract
During the past ten years, the energy consumption problem in cloud-related environments has attracted substantial attention in research and industrial communities. Researchers have conducted many surveys on energy efficiency issues from different perspectives. All of the surveys can be classified into five categories: surveys on the energy efficiency of the whole cloud related system, surveys on the energy efficiency of a certain level or component of the cloud, surveys on all of the energy efficient strategies, surveys on a certain energy efficiency techniques, and other energy efficiency related surveys. However, to the best of our knowledge, surveys on energy-aware data management strategies in cloud-related environment are absent. In this paper, we conduct a comprehensive survey on energy saving-aware data management strategies in cloud-related environments, such as data classification, data placement and data replication strategies. Compared to current existing reviews on energy efficiency in cloud-related environments, we firstly conduct the survey on the energy consumption problem from the data management perspective. Furthermore, we classify the energy-aware data management strategies from different perspectives. This survey and the taxonomy of the energy-aware data management strategies demonstrate the potential for reducing the energy consumption at the data management level of a cloud storage system, which will compress more space for energy reduction and finally achieve energy proportionality. Moreover, this survey and taxonomy on the energy efficiency issue from the data management perspective is an important supplement to current existing surveys on energy efficiency in cloud-related environments.
Highlights
Energy consumption is one of the most serious problems in cloud-related environments, especially in datacenter part
To discover more opportunities to reduce the energy consumption in data centers, we focus on the lack of surveys on energy-aware data management strategies in cloud related environments
Inspired by the work of Kuashik’s team, we have proposed a green data classification strategy based on anticipation named AGDC, in which a neural network is employed to predict the temperature of the data
Summary
Energy consumption is one of the most serious problems in cloud-related environments, especially in datacenter part. X. You et al.: Survey and Taxonomy on Energy-Aware Data Management Strategies in Cloud Environment conducted in this paper, which is an important supplement for the current energy efficiency relevant surveys. The survey and taxonomy on improving energy efficiency utilizing the data management strategies, such as data classification, data placement and data replication, can offer more opportunities to reduce the energy consumption in cloudrelated environments, especially for data-intensive related applications in the scale-growing data centers. The survey and taxonomy of energy-aware data management strategies in cloud-related environments are II. To discover more opportunities to reduce the energy consumption in data centers, we focus on the lack of surveys on energy-aware data management strategies in cloud related environments.
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