A Survey and Taxonomy on Energy-Aware Data Management Strategies in Cloud Environment

被引:11
作者
You, Xindong [1 ]
Lv, Xueqiang [1 ]
Zhao, Zhikai [2 ]
Han, Junmei [3 ]
Ren, Xueping [4 ]
机构
[1] Beijing Informat Sci & Technol Univ, Beijing Key Lab Internet Culture & Digital Dissem, Beijing 100101, Peoples R China
[2] China Univ Min & Technol, Internet Things IoT Res Ctr, Natl Joint Engn Lab Internet Appl Technol Mines, Xuzhou 221008, Jiangsu, Peoples R China
[3] PLA, Inst Syst Engn, AMS, Lab Complex Syst, Beijing 100102, Peoples R China
[4] Hangzhou Dianzi Univ, Minist Educ, Key Lab Complex Syst Modeling & Simulat, Hangzhou 310037, Peoples R China
来源
IEEE ACCESS | 2020年 / 8卷
基金
中国国家自然科学基金;
关键词
Energy consumption; cloud storage system; data classification; data placement; data replication; energy proportionality; DATA REPLICATION; DATA PLACEMENT; DATA CENTERS; EFFICIENCY; MECHANISM; SYSTEMS;
D O I
10.1109/ACCESS.2020.2992748
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:94279 / 94293
页数:15
相关论文
共 135 条
  • [1] Ahuja Sanjay P., 2016, International Journal of Green Computing, V7, P25, DOI 10.4018/IJGC.2016010102
  • [2] An Energy-aware Virtual Machine Migration Algorithm
    Al Shayeji, Mohammad H.
    Samrajesh, M. D.
    [J]. 2012 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING AND COMMUNICATIONS (ICACC), 2012, : 242 - 246
  • [3] Amur H., 2010, Proceedings of the 1st ACM symposium on Cloud computing, P217
  • [4] [Anonymous], 2017, HDB RES END TO END C
  • [5] [Anonymous], 2015, P 6 ACM S CLOUD COMP
  • [6] [Anonymous], 2015, EUROP J ADV ENG TECH
  • [7] [Anonymous], [No title captured]
  • [8] [Anonymous], [No title captured]
  • [9] [Anonymous], 2019, IEEE T MED IMAGING, DOI DOI 10.1109/TMI.2018.2867261
  • [10] [Anonymous], 2008, P C POW AW COMP SYST