DocumentCode :
3366839
Title :
An Energy-Aware Optimization Model Based on Data Placement and Task Scheduling
Author :
Xiaoli Wang ; Yuping Wang ; Kun Meng
Author_Institution :
Sch. of Comput. Sci. & Technol., Xidian Univ., Xi´an, China
fYear :
2013
fDate :
14-15 Dec. 2013
Firstpage :
45
Lastpage :
49
Abstract :
Recently, technologies on reducing energy consumption of data centers have drawn considerable attentions. One constructive way is to improve energy efficiency of servers. Aiming at this goal, we propose a new energy-aware optimization model based on the combination of data placement and task scheduling in this paper. The main contributions are: (1)The impact of servers´ performance on energy consumption is explored. (2) The model guarantees 100% data locality to save network bandwidth. (3) As tasks involved in cloud computing are usually tens of thousands, in order to solve this large scale optimization model efficiently, specific-design encoding and decoding methods are introduced. Based on these, an effective evolutionary algorithm is proposed. Finally, numerical experiments are made and the results indicate the effectiveness of the proposed algorithm.
Keywords :
cloud computing; computer centres; data handling; energy conservation; energy consumption; evolutionary computation; power aware computing; cloud computing; data centers; data locality; data placement; design decoding methods; design encoding methods; energy consumption reduction; energy efficiency; energy-aware optimization model; evolutionary algorithm; large scale optimization model; network bandwidth; server performance; task scheduling; Data models; Energy consumption; Genetic algorithms; Optimization; Resource management; Servers; Vectors; Bi-level optimization; Data locality; Data placement; Energy-aware; Large-scale task scheduling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Security (CIS), 2013 9th International Conference on
Conference_Location :
Leshan
Print_ISBN :
978-1-4799-2548-3
Type :
conf
DOI :
10.1109/CIS.2013.17
Filename :
6746353
Link To Document :
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