An overview of energy efficiency techniques in cluster computing systems

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• 作者：Giorgio Luigi Valentini (1) (11)
  Walter Lassonde (1)
  Samee Ullah Khan (1)
  Nasro Min-Allah (2)
  Sajjad A. Madani (2)
  Juan Li (1)
  Limin Zhang (1)
  Lizhe Wang (3)
  Nasir Ghani (4)
  Joanna Kolodziej (5)
  Hongxiang Li (6)
  Albert Y. Zomaya (7)
  Cheng-Zhong Xu (8)
  Pavan Balaji (9)
  Abhinav Vishnu (10)
  Fredric Pinel (11)
  Johnatan E. Pecero (11)
  Dzmitry Kliazovich (11)
  Pascal Bouvry (11)
  
• 关键词：Cluster computing ; Energy efficiency ; Power management ; Survey
• 刊名：Cluster Computing
• 出版年：2013
• 出版时间：March 2013
• 年：2013
• 卷：16
• 期：1
• 页码：3-15
• 全文大小：812 KB
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• 作者单位：Giorgio Luigi Valentini (1) (11)
  Walter Lassonde (1)
  Samee Ullah Khan (1)
  Nasro Min-Allah (2)
  Sajjad A. Madani (2)
  Juan Li (1)
  Limin Zhang (1)
  Lizhe Wang (3)
  Nasir Ghani (4)
  Joanna Kolodziej (5)
  Hongxiang Li (6)
  Albert Y. Zomaya (7)
  Cheng-Zhong Xu (8)
  Pavan Balaji (9)
  Abhinav Vishnu (10)
  Fredric Pinel (11)
  Johnatan E. Pecero (11)
  Dzmitry Kliazovich (11)
  Pascal Bouvry (11)
  
  1. NDSU-CIIT Green Computing and Communications Laboratory, Department of Electrical and Computer Engineering, North Dakota State University, Fargo, ND, 58108-6050, USA
  11. University of Luxembourg, Luxembourg, L1359, Luxembourg
  2. COMSATS Institute of Information Technology, Islamabad, Pakistan
  3. Indiana University, Bloomington, IN, USA
  4. University of New Mexico, Albuquerque, NM, USA
  5. University of Bielsko-Biala, 43300, Bielsko-Biala, Poland
  6. University of Louisville, Louisville, KY, USA
  7. University of Sydney, Sydney, NSW, 2006, Australia
  8. Wayne State University, Detroit, MI, USA
  9. Argonne National Laboratory, Argonne, IL, USA
  10. Pacific Northwest National Laboratory, Richland, WA, USA
  
• ISSN：1573-7543

文摘

Two major constraints demand more consideration for energy efficiency in cluster computing: (a)?operational costs, and (b) system reliability. Increasing energy efficiency in cluster systems will reduce energy consumption, excess heat, lower operational costs, and improve system reliability. Based on the energy-power relationship, and the fact that energy consumption can be reduced with strategic power management, we focus in this survey on the characteristic of two main power management technologies: (a)?static power management (SPM) systems that utilize low-power components to save the energy, and (b) dynamic power management (DPM) systems that utilize software and power-scalable components to optimize the energy consumption. We present the current state of the art in both of the SPM and DPM techniques, citing representative examples. The survey is concluded with a brief discussion and some assumptions about the possible future directions that could be explored to improve the energy efficiency in cluster computing.