A Novel Task Scheduling Approach for Reducing Energy Consumption of MapReduce Cluster

被引：12

作者：

Song, Jie ^{[1
]}

Liu, Xuebing ^{[1
]}

Zhu, Zhiliang ^{[1
]}

Zhao, Dazhe ^{[2
]}

Yu, Ge ^{[3
]}

机构：

[1] Northeastern Univ, Coll Software, Shenyang 110819, Peoples R China

[2] Northeastern Univ, Software Ctr, Shenyang 110819, Peoples R China

[3] Northeastern Univ, Sch Informat & Engn, Shenyang 110819, Peoples R China

来源：

IETE TECHNICAL REVIEW | 2014年 / 31卷 / 01期

基金：

中国国家自然科学基金; 新加坡国家研究基金会;

关键词：

Energy efficiency; MapReduce; Resource allocation; Task scheduling;

D O I：

10.1080/02564602.2014.890846

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

080906 [电磁信息功能材料与结构]; 082806 [农业信息与电气工程];

摘要：

In recent years, data processing technologies like MapReduce in cloud computing have been widely used. However, the problem of high energy consumption (EC) is an obstacle for further development of cloud computing. We believe that EC could be reduced not only by hardware reinforcement but also by software improvement, especially, by energy-aware task scheduling. In this paper, the Best resources assignment model (Bram) is proposed. On this basis, a scheduling approach, concerning resource usage of nodes and different kinds of resource intensive tasks running on them, is proposed to avoid resource idleness, and then reduce energy consumption. The experimental results show that the new method could reduce the energy consumption of MapReduce cluster.

引用

页码：65 / 74

页数：10

共 15 条

[1]

Elnozahy EN, 2003, LECT NOTES COMPUT SC, V2325, P179

[2]

Harizopoulos S., 2009, CIDR

[3]

Save Watts in your Grid: Green Strategies for Energy-Aware Framework in Large Scale Distributed Systems [J].

Orgerie, Anne-Cecile ;

Lefevre, Laurent ;

Gelas, Jean-Patrick .

PROCEEDINGS OF THE 2008 14TH IEEE INTERNATIONAL CONFERENCE ON PARALLEL AND DISTRIBUTED SYSTEMS, 2008, :171-178

[4]

Pinheiro Eduardo., 2001, Proceedings of the Workshop on Compilers and Operating Systems for Low Power, P182

[5]

Song J., 2013, J ZHEJIANG U, V43, P44

[6]

Study on energy-consumption regularities of cloud computing systems by a novel evaluation model [J].

Song, Jie ;

Li, Tiantian ;

Wang, Zhi ;

Zhu, Zhiliang .

COMPUTING, 2013, 95 (04) :269-287

[7]

Energy-efficiency model and measuring approach for cloud computing [J].

Song, Jie ;

Li, Tian-Tian ;

Yan, Zhen-Xing ;

Na, Jun ;

Zhu, Zhi-Liang .

Ruan Jian Xue Bao/Journal of Software, 2012, 23 (02) :200-214

[8]

Srikantaiah S., 2008, USENIX HotPower'08: Workshop on Power Aware Computing and Systems at OSDI

[9]

Tao Zhu, 2011, Proceedings of the 2011 12th International Conference on Parallel and Distributed Computing Applications and Technologies (PDCAT 2011), P319, DOI 10.1109/PDCAT.2011.42

[10]

Survey on Energy-Efficient Data Management [J].

Wang, Jun ;

Feng, Ling ;

Xue, Wenwei ;

Song, Zhanjiang .

SIGMOD RECORD, 2011, 40 (02) :17-23

← 1 2 →