Power Usage Effectiveness Metrics to Measure Efficiency and Performance of Data Centers

Intensifying computation demand from enterprises has driven the growth of large, multifaceted data centers to manage current Internet, financial, commercial, and business applications. A d ata center comprises thousands of servers and other equipment that require substantial amounts of power to operate. This condition resu lts in numerous challenges for the data center industry, such as massive energy consumption, underutilization of installed equipment, emission of greenhouse gases, and effect on global warming. This paper highlights the significance of identifying metrics to determine the pe rformance and efficiency of a data center, which can help such a facility achieve operational cost savings through proper implementation of performance-measuring metrics. This paper discusses the implementation of Power Usage Effectiveness metrics in a tier-level data center in Pakistan. The results show that the overall performance value of the facility is 3.3, which indicates poor and inefficient operations.

[1]  Frank Bellosa,et al.  Resource-conscious scheduling for energy efficiency on multicore processors , 2010, EuroSys '10.

[2]  Daniel Kharitonov,et al.  Power Saving Strategies and Technologies in Network Equipment Opportunities and Challenges, Risk and Rewards , 2008, 2008 International Symposium on Applications and the Internet.

[3]  Christian Belady,et al.  GREEN GRID DATA CENTER POWER EFFICIENCY METRICS: PUE AND DCIE , 2008 .

[4]  Jan Broeckhove,et al.  An Evaluation of the Benefits of Fine-Grained Value-Based Scheduling on General Purpose Clusters , 2010, 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing.

[5]  Christopher G. Malone,et al.  Metrics and an Infrastructure Model to Evaluate Data Center Efficiency , 2007 .

[6]  M. Adachi,et al.  A Study on a Resource Allocation Algorithm for On-demand Data Center Services , 2008, 2008 10th International Conference on Advanced Communication Technology.

[7]  Lizhe Wang,et al.  Review of performance metrics for green data centers: a taxonomy study , 2011, The Journal of Supercomputing.

[8]  Jason Harris Green Computing and Green IT Best Practices on Regulations and Industry Initiatives, Virtualization, Power Management, Materials Recycling and Telecommuting , 2008 .

[9]  Xin Luo,et al.  Integrative framework for assessing firms' potential to undertake Green IT initiatives via virtualization - A theoretical perspective , 2011, J. Strateg. Inf. Syst..

[10]  Parthasarathy Ranganathan,et al.  Models and Metrics for Energy-Efficient Computing , 2009, Adv. Comput..

[11]  Tao Lu,et al.  Investigation of air management and energy performance in a data center in Finland: Case study , 2011 .

[12]  Christoforos E. Kozyrakis,et al.  JouleSort: a balanced energy-efficiency benchmark , 2007, SIGMOD '07.

[13]  Viet T. Dao,et al.  From green to sustainability: Information Technology and an integrated sustainability framework , 2011, J. Strateg. Inf. Syst..

[14]  Ricardo Lent,et al.  A model for network server performance and power consumption , 2013, Sustain. Comput. Informatics Syst..

[15]  Ricardo Bianchini,et al.  Energy conservation in heterogeneous server clusters , 2005, PPoPP.

[16]  Christoforos E. Kozyrakis,et al.  A Comparison of High-Level Full-System Power Models , 2008, HotPower.

[17]  Christoforos E. Kozyrakis,et al.  Automatic power management schemes for Internet servers and data centers , 2005, GLOBECOM '05. IEEE Global Telecommunications Conference, 2005..

[18]  Anand Sivasubramaniam,et al.  Profiling, Prediction, and Capping of Power Consumption in Consolidated Environments , 2008, 2008 IEEE International Symposium on Modeling, Analysis and Simulation of Computers and Telecommunication Systems.

[19]  Azizah Abdul Rahman,et al.  Techniques to implement in green data centres to achieve energy efficiency and reduce global warming effects , 2011 .

[20]  E. N. Elnozahy,et al.  Energy-Efficient Server Clusters , 2002, PACS.

[21]  Azizah Abdul Rahman,et al.  Energy efficiency and low carbon enabler green it framework for data centers considering green metrics , 2012 .

[22]  Siew Eang Lee,et al.  Case study of data centers’ energy performance , 2006 .

[23]  John P. Weyant,et al.  On the sources of technological change: Assessing the evidence , 2006 .

[24]  Krishna Kant,et al.  Data center evolution: A tutorial on state of the art, issues, and challenges , 2009, Comput. Networks.

[25]  Jonathan G. Koomey,et al.  The risk of surprise in energy technology costs , 2007 .

[26]  Asadullah Shah,et al.  Green Information Technology (IT) framework for energy efficient data centers using virtualization , 2012 .

[27]  Joe Loper,et al.  Energy efficiency in data centers: A new policy frontier , 2007 .

[28]  Arnold L. Rosenberg,et al.  Application Placement on a Cluster of Servers , 2007, Int. J. Found. Comput. Sci..

[29]  J. Koomey Worldwide electricity used in data centers , 2008 .

[30]  Chandra Kopparapu,et al.  Load Balancing Servers, Firewalls, and Caches , 2002 .

[31]  Klara Nahrstedt,et al.  Energy-efficient soft real-time CPU scheduling for mobile multimedia systems , 2003, SOSP '03.

[32]  Daniel Mossé,et al.  Power optimization for dynamic configuration in heterogeneous web server clusters , 2010, J. Syst. Softw..

[33]  Georges Da Costa,et al.  2005 IEEE International Symposium on Cluster Computing and the Grid , 2005, CCGRID.

[34]  Chandrakant D. Patel,et al.  B13-115 A VISION OF ENERGY AWARE COMPUTING FROM CHIPS TO DATA CENTERS , 2003 .

[35]  Kwok Kee Wei,et al.  Adopting organizational virtualization in B2B firms: An empirical study in Singapore , 2008, Inf. Manag..

[36]  James Laudon,et al.  Performance/Watt: the new server focus , 2005, CARN.

[37]  Leslie P. Willcocks,et al.  A review of the IT outsourcing literature: Insights for practice , 2009, J. Strateg. Inf. Syst..

[38]  Kevin Skadron,et al.  Energy management in real-time multi-tier internet services , 2008 .

[39]  Ricardo Bianchini,et al.  Power and energy management for server systems , 2004, Computer.

[40]  Hakan Aydin,et al.  Energy-aware task allocation for rate monotonic scheduling , 2005, 11th IEEE Real Time and Embedded Technology and Applications Symposium.

[41]  Jonathan G. Koomey,et al.  Data Centers Revisited: Assessment of the Energy Impact of Retrofits and Technology Trends in a High-Density Computing Facility , 2004 .

[42]  Daniel Mossé,et al.  A dynamic configuration model for power-efficient virtualized server clusters , 2009 .