DocumentCode
2868532
Title
A Power-Aware Scheduling of MapReduce Applications in the Cloud
Author
Li, Ying ; Zhang, Hongli ; Kim, Kyong Hoon
Author_Institution
Dept. of Inf., Gyeongsang Nat. Univ., Jinju, South Korea
fYear
2011
fDate
12-14 Dec. 2011
Firstpage
613
Lastpage
620
Abstract
Cloud computing is an emerging computing technology for large data center that maintains computational resources through the internet, rather than on local computers. The large data centers maintain Cloud computing applications with lots of cost because of power consumption, which results in a new research issue, called Green Cloud computing. Since MapReduce is one of popular Cloud computing models, this paper focuses on how to reduce energy of MapReduce applications. Thus, we propose a new power-aware MapReduce application model to be used for power-aware computing with consideration of users´ requirements. We also provide a scheduling algorithm for MapReduce applications in heterogeneous Cloud resources and suggest power-aware schemes in order to reduce the total energy. Throughout simulation results, we show that the proposed scheduling algorithm saves more energy than static schemes.
Keywords
cloud computing; distributed processing; power aware computing; scheduling; Internet; MapReduce applications; computational resources; data center; green cloud computing; heterogeneous cloud resources; power consumption; power-aware MapReduce application model; power-aware computing; power-aware scheduling; total energy reduction; Biological system modeling; Cloud computing; Computational modeling; Mathematical model; Power demand; Scheduling algorithm; Cloud; MapReduce; power-aware; scheduling;
fLanguage
English
Publisher
ieee
Conference_Titel
Dependable, Autonomic and Secure Computing (DASC), 2011 IEEE Ninth International Conference on
Conference_Location
Sydney, NSW
Print_ISBN
978-1-4673-0006-3
Type
conf
DOI
10.1109/DASC.2011.111
Filename
6119057
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