Journal of Computer Applications ›› 2015, Vol. 35 ›› Issue (1): 39-42.DOI: 10.11772/j.issn.1001-9081.2015.01.0039

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Optimal power consumption of heterogeneous servers in cloud center under performance constraint

HE Huaiwen1,2, FU Yu1, YANG Liang1, YANG Yihong3   

  1. 1. School of Computer, Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan Guangdong 528402, China;
    2. School of Information Science and Technology, Sun Yat-sen University, Guangzhou Guangdong 510275, China;
    3. Beijing Institute of Technology, ZHUHAI, Zhuhai Guangdong 519088, China
  • Received:2014-08-04 Revised:2014-09-15 Online:2015-01-01 Published:2015-01-26

性能受限下云中心异构服务器的能耗优化

何怀文1,2, 傅瑜1, 杨亮1, 杨毅红3   

  1. 1. 电子科技大学中山学院 计算机学院, 广东 中山528402;
    2. 中山大学 信息科学与技术学院, 广州510275;
    3. 北京理工大学 珠海学院, 广东 珠海519088
  • 通讯作者: 何怀文
  • 作者简介:何怀文(1980-),男,广西北海人,讲师,博士研究生,主要研究方向:云计算、资源分配、随机优化;傅瑜(1962-),男,陕西西安人,主要研究方向:模式识别、网络安全;杨亮(1980-),男,江西婺源人,讲师,博士研究生,主要研究方向:智能控制、优化算法;杨毅红(1982-),女,广西河池人,讲师,博士,主要研究方向:气象模型、数值计算.
  • 基金资助:

    国家自然科学基金资助项目(61300095);广东省自然科学基金资助项目(S2012010010508, S2013010012307);中山市科技计划项目(2013A3FC0285, 2014A2FC396).

Abstract:

For the problem of minimizing the energy consumption under performance constraint of cloud center, an optimal power consumption allocation method among multiple heterogeneous servers was proposed. First, an optimal energy consumption mathematical model of cloud center was built. Second, a Minimizing Power Consumption (MPC) algorithm for calculating the minimum energy was developed by using Lagrange multiplier method to obtain the optimal solution of the model. Finally, the MPC algorithm was verified by plenty of numerical experiments and compared with the Equal-Power (EP) baseline method. The experimental results indicate that MPC algorithm can save approximately 30% energy than the EP baseline method under the same load and the same response time conditions, and the proportion of energy saving will increase with load increasing. The MPC algorithm can effectively avoid energy configuration overload and it will provide ideas and reference data for optimal resource allocation of cloud center.

Key words: cloud center, heterogeneous server, performance constraint, processor sharing, queuing system

摘要:

针对保证云中心性能下最小化能耗的问题,提出云中心异构服务器之间优化能耗分配方法.首先,建立云中心能耗优化的数学模型;然后,通过拉格朗日乘子法获取该模型的最优解,得到计算最小能量的最小能耗(MPC)算法;最后,通过大量数值实验进行算法验证并与功耗相等分配(EP)基准方法进行了比较.实验结果表明:在相同负载、相同响应时间约束下,MPC算法比EP基准方法节省近30%的能耗,并随着负载增加节省能耗的比例更高.MPC算法可有效避免云中心能源配置过载,为云中心资源优化配置提供思路和参考数据.

关键词: 云中心, 异构服务器, 性能受限, 处理器共享, 排队系统

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