Back to Search Start Over

基于遗传算法的数据中心能效仿真.

Authors :
毛媛媛
石恩雅
蒋从锋
仇烨亮
贾刚勇
万"健
闫龙川
Source :
Computer Engineering & Science / Jisuanji Gongcheng yu Kexue. Aug2021, Vol. 43 Issue 8, p1341-1352. 12p.
Publication Year :
2021

Abstract

With the continuous expansion of the number and scale of data centers, energy consumption has become a key issue that restricts the cost and reliability of data centers. Moreover, with the iterative updates of the hardware after the data center is put into operation, the heterogeneity of the data center server has further increased, and its energy efficiency has also under gone major changes compared with the initial design and construction. Therefore, according to the structure and hard ware configuration of the data center server, the dynamic energy efficiency simulation and analysis of the entire data center will help to grasp the energy efficiency status of the data center in real time, carry out energy efficiency aware load scheduling, and provide the possibility of energy efficiency optimization. Based on the SPECpower test results of enterprise-level servers, this article first analyzes the energy efficiency development trends and influencing factors of servers in recent years. Secondly, based on the genetic algorithm, the energy efficiency optimization of the data center is simulated, and a prototype system of the energy efficiency simulator of the data center is designed. The simulator can dynamically simulate and adjust the operating status of data center servers according to power supply limits, load conditions, throughput indicators, etc., and simulate the energy efficiency of data center s of different sizes and types of servers. The proposed data center energy efficiency simulation algorithm based on genetic algorithm obtains smaller errors and shorter simulation calculation time in the energy minimization problem. [ABSTRACT FROM AUTHOR]

Details

Language :
Chinese
ISSN :
1007130X
Volume :
43
Issue :
8
Database :
Academic Search Index
Journal :
Computer Engineering & Science / Jisuanji Gongcheng yu Kexue
Publication Type :
Academic Journal
Accession number :
152665166
Full Text :
https://doi.org/10.3969/j.issn.1007-130X.2021.08.002