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    Abstract
2013 (Vol. 5, Issue: 22)
Article Information:

Based on the MapReduce Model for Data-intensive Computing of Energy Scheduling Algorithm Strategy

Yuqiang Sun, 1Xin Gao, Huanhuan Cai, Xianmei Chang and Lei Li
Corresponding Author:  Yuqiang Sun 

Key words:  Data-intensive, MapReduce, scheduling algorithm, , , ,
Vol. 5 , (22): 5267-5271
Submitted Accepted Published
October 22, 2012 December 28, 2012 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.
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  Cite this Reference:
Yuqiang Sun, 1Xin Gao, Huanhuan Cai, Xianmei Chang and Lei Li, 2013. Based on the MapReduce Model for Data-intensive Computing of Energy Scheduling Algorithm Strategy.  Research Journal of Applied Sciences, Engineering and Technology, 5(22): 5267-5271.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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