Research Article | OPEN ACCESS
Based on the MapReduce Model for Data-intensive Computing of Energy Scheduling Algorithm Strategy
1, 2Yuqiang Sun, 1Xin Gao, 1Huanhuan Cai, 1Xianmei Chang and 1Lei Li
1International Institute of Ubiquitous Computing, Chang Zhou University, Chang Zhou 213164, China
2School of Computer and Information Technology, Henan Normal University,
Hennan, Xinxiang 453007, China
Research Journal of Applied Sciences, Engineering and Technology 2013 22:5267-5271
Received: October 22, 2012 | Accepted: December 28, 2012 | Published: May 25, 2013
Abstract
In this study, based on the consideration of energy consumption, we take to improve the strategy of the MapReduce job scheduling algorithm, in order to reduce the average response time for task scheduling of interactive jobs in the network. In accordance with the job priority grouping to adjust the scheduling task response time which can reduce the impact of network congestion, with good results that increase the throughput of the system transferring data and computing power.
Keywords:
Data-intensive, MapReduce, scheduling algorithm,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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