基于PE方法的数据中心需量费用优化算法

黄焱; 王鹏; 谢高辉

doi:10.11959/j.issn.1000-436x.2016056

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基于PE方法的数据中心需量费用优化算法

学术论文 | 更新时间：2024-06-05

- 基于PE方法的数据中心需量费用优化算法
- Optimizing demand charge of data center base on PE method
- 通信学报 2016年37卷第3期页码：90-97
- 作者机构：
  
  1. 中国科学院成都计算机应用研究所，四川成都 610041
  2. 中国科学院大学，北京 100049
  3. 西南民族大学计算机科学与技术学院，四川成都 610041
  4. 广州五舟科技股份有限公司，广东广州 510000
- 作者简介：
  
  [ "黄焱（1982-），男，江苏泗阳人，中国科学院成都计算机应用研究所博士生，主要研究方向为智能算法、最优化理论等。" ]
  [ "王鹏（1975-），男，四川犍为人，西南民族大学教授、博士生导师，主要研究方向为智能算法、高性能计算等。" ]
  [ "谢高辉（1979-），男，湖南郴州人，广州五舟科技股份有限公司总经理，主要研究方向为高性能计算。" ]
- 基金信息：
  
  国家自然科学基金资助项目(60702075);广东省科技厅高新技术产业化科技攻关基金资助项目(2011B010200007);成都市创新发展战略研究基金资助项目(11RKYB016ZF)
- DOI：10.11959/j.issn.1000-436x.2016056
  中图分类号： TP393
- 网络出版日期：2016-03，
  
  纸质出版日期：2016-03-25
- 稿件说明：
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黄焱, 王鹏, 谢高辉. 基于PE方法的数据中心需量费用优化算法[J]. 通信学报, 2016,37(3):90-97.

Yan HUANG, Peng WANG, Gao-hui XIE. Optimizing demand charge of data center base on PE method[J]. Journal on communications, 2016, 37(3): 90-97.
黄焱, 王鹏, 谢高辉. 基于PE方法的数据中心需量费用优化算法[J]. 通信学报, 2016,37(3):90-97. DOI： 10.11959/j.issn.1000-436x.2016056.

Yan HUANG, Peng WANG, Gao-hui XIE. Optimizing demand charge of data center base on PE method[J]. Journal on communications, 2016, 37(3): 90-97. DOI： 10.11959/j.issn.1000-436x.2016056.

摘要

数据中心的电费包含需量费用和用量费用2个部分，以往的数据中心电费优化研究通常未考虑需量费用。在满足服务质量和响应时间的约束条件下采用PE(partial execution)方法可以减少峰值功率，从而降低需量费用。通过对时间、外部负载、服务质量约束、响应时间约束进行建模，构建电费优化问题的模型，提出基于 PE 方法的需量费用优化算法PEDC（partial execution demand charge)，在高负载时间段执行PE方法减小峰值功率以降低需量费用并降低用量费用，从而降低数据中心的总电费。通过与4种算法进行比较，并构造准确预测的负载数据对PEDC算法性能进行测试，PEDC算法可以降低数据中心运营总电费5.9%~12.7%，提升集群使用率1.32倍。

Abstract

Demand charge and energy charge are the two main components of data center electricity cost

previous re-searches have not take demand charge into consideration.PEDC algorithm was proposed by modeling time slot

work-load

service quality constraint and response time constraint.With PEDC algorithm peak power was decreased by partial execution on the condition of service quality constrai and response time constraint.PE method was executed in the heavy loaded time slots to reduce peak power so as to ize demand charge.Energy charge and total charge were also optimized.By comparing with four algorithms and with accurately predicted

PEDC algorithm can reduce elec-tricity cost by 5.9%~12.7% and improve cluster utilization 1.32 times.

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references

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