A taxonomy of software-based and hardware-based approaches for energy efficiency management in the Hadoop. (15th January 2019)

• Record Type: Journal Article
• Authors: Shabestari, Fatemeh; Rahmani, Amir Masoud; Navimipour, Nima Jafari; Jabbehdari, Sam
• Is Part Of: Journal of network and computer applications. Volume 126(2019)
• Page Start: 162
• Page End: 177
• Publication Date: 2019-01-15
• Subjects: Hadoop -- Energy efficiency -- MapReduce -- HDFS -- YARN -- Big data; Microcomputers -- Periodicals; Computer networks -- Periodicals; Application software -- Periodicals; Micro-ordinateurs -- Périodiques; Réseaux d'ordinateurs -- Périodiques; Logiciels d'application -- Périodiques; Application software; Computer networks; Microcomputers; Periodicals; 004.05; 004
• DOI: 10.1016/j.jnca.2018.11.007
• Languages: English
• ISSNs: 1084-8045

Abstract

Abstract: 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.