A taxonomy of software-based and hardware-based approaches for energy efficiency management in the Hadoop

被引:30
作者
Shabestari, Fatemeh [1 ]
Rahmani, Amir Masoud [1 ]
Navimipour, Nima Jafari [2 ]
Jabbehdari, Sam [3 ]
机构
[1] Islamic Azad Univ, Dept Comp Engn, Sci & Res Branch, Tehran, Iran
[2] Islamic Azad Univ, Tabriz Branch, Dept Comp Engn, Tabriz, Iran
[3] Islamic Azad Univ, North Tehran Branch, Dept Comp Engn, Tehran, Iran
关键词
Hadoop; Energy efficiency; MapReduce; HDFS; YARN; Big data; RESOURCE-ALLOCATION; SCHEDULING APPROACH; APACHE HADOOP; MAPREDUCE; PERFORMANCE; CONSUMPTION; OPTIMIZATION; SYSTEMS; MECHANISMS; ASSIGNMENT;
D O I
10.1016/j.jnca.2018.11.007
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Apache Hadoop framework supports the storing and processing of big data datasets using simple programming models. Energy management has been recognized as one of the major issues in Hadoop, and many types of research have been conducted in this scope. However, despite the importance of this issue, there is no inclusive study about energy efficiency in Hadoop. In this paper, the techniques of energy efficiency in Hadoop are classified into two main categories. Moreover, the benefits and drawbacks of these methods and a systematic study of the conducted research are provided and examined in this paper. Another aim is to provide the visions for the descriptions of open issues and recommendations for future research.
引用
收藏
页码:162 / 177
页数:16
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