Globally CO2 emissions attributable to Information Technology are on par with those resulting from aviation. Recent growth in cloud service demand has elevated energy efficiency of data centers to a critical area within green computing. Cloud computing represents a backbone of IT services and recently there has been an increase in high-definition multimedia delivery, which has placed new burdens on energy resources. Hardware innovations together with energy-efficient techniques and algorithms are key to controlling power usage in an ever-expanding IT landscape. This special issue contains a number of contributions that show that data center energy efficiency should be addressed from diverse vantage points. © 2017 by the authors. Licensee MDPI, Basel, Switzerland

Bein, Wolfgang W.

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Computer Science Faculty Publications Computer Science 1-9-2018 Energy Saving In Data Centers Wolfgang W. Bein University of Nevada, Las Vegas, wolfgang.bein@unlv.edu Follow this and additional works at: https://digitalscholarship.unlv.edu/compsci_fac_articles  Part of the Computer Sciences Commons Repository Citation Bein, W. W. (2018). Energy Saving In Data Centers. Electronics, 7 1-3. http://dx.doi.org/10.3390/electronics7010005 This Article is protected by copyright and/or related rights. It has been brought to you by Digital Scholarship@UNLV with permission from the rights-holder(s). You are free to use this Article in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s) directly, unless additional rights are indicated by a Creative Commons license in the record and/or on the work itself.  This Article has been accepted for inclusion in Computer Science Faculty Publications by an authorized administrator of Digital Scholarship@UNLV. For more information, please contact digitalscholarship@unlv.edu. electronicsEditorialEnergy Saving in Data CentersWolfgang BeinCenter for Information Technology and Algorithms, Department of Computer Science, University of Nevada,Las Vegas, NV 89154, USA; wolfgang.bein@unlv.edu; Tel.: +1-702-895-1477Received: 29 December 2017; Accepted: 4 January 2018; Published: 9 January 2018Abstract: Globally CO2 emissions attributable to Information Technology are on par with thoseresulting from aviation. Recent growth in cloud service demand has elevated energy efficiency ofdata centers to a critical area within green computing. Cloud computing represents a backbone ofIT services and recently there has been an increase in high-definition multimedia delivery, whichhas placed new burdens on energy resources. Hardware innovations together with energy-efficienttechniques and algorithms are key to controlling power usage in an ever-expanding IT landscape.This special issue contains a number of contributions that show that data center energy efficiencyshould be addressed from diverse vantage points.Keywords: sustainability; data centers; cloud computing; renewable energy; energy efficiency;green computing1. IntroductionSustainability, as defined by the National Science Board (NSB), involves meeting present needswithout compromising the ability of future generations to meet their own needs. According to the NSBsustainability cuts across disciplinary boundaries, because it has many aspects that cannot be addressedby individual disciplines [1]. With the imperative to limit carbon emissions, energy efficiency hastaken on renewed urgency. The chief executive officer of Google remarked, “What matters most to thecomputer designers at Google is not speed but power, low power, because data centers can consumeas much energy as a city” [2]. Cloud computing now represents a backbone of IT services and recentlythere has been an increase in high-definition multimedia delivery, which has placed new burdens onenergy resources. Energy demands have motivated research on energy efficiency strategies and theimplementation of renewable energy sources as to reduce operational costs and environmental impact.The ever-increasing scale of data centers has presented unprecedented challenges for hardware andalgorithmic development.This special issue aimed to present a wide range of papers with contributions in the area of greencloud computing. Contributions bringing together hardware challenges and algorithmic approacheswere especially encouraged and we were interested in submissions from researchers who work at theintersection of Electrical Engineering, Modeling and Simulation, and Computer Science.2. Putting Energy Usage of Data Centers in PerspectiveAccording to the 2016 United States Data Center Energy Usage Report [3] (published by U.S.Department of Energy under a Lawrence Berkeley National Laboratory Contract), data centers in theU.S. consumed an estimated 70 billion kWh in 2014—the year studied in the report. This representsabout 1.8% of total U.S. electricity consumption. Globally CO2 emissions attributable to IT are onpar with those of aviation with 70.9 MMTCO2 in 2011 [4,5]. It is noteworthy that energy efficiencymeasures have already stemmed energy demand increases despite the tremendous growth in big data:data centers electricity consumption increased by about 4% from 2010 to 2014, less than the roughly24% percent increase in the previous five years and much less than 90% five-year increase prior to that.Electronics 2018, 7, 5; doi:10.3390/electronics7010005 www.mdpi.com/journal/electronicsElectronics 2018, 7, 5 2 of 3Indeed, current growth is mainly attributable to very large “hyper-scale” datacenters used for largecloud facilities. Energy-efficient techniques and algorithms are key to controlling power usage in anever-expanding IT landscape.Efficiency gains have been achieved across the gamut from improved hardware, server powerscaling, refined operating systems, efficient use of virtualization, geographical workload distribution,advanced resource management, and the preferred use of renewable energy. Areas of interest aredata center sustainability, dependability and cost, energy reduction in server systems, energy-awareresource allocation, energy-optimized multimedia clouds, thermal states and cooling system operation,power-down management, burdened energy management, dynamic voltage and frequency scaling,dynamic component deactivation, load balancing power for cluster-based systems, power managementin virtual cloud environments, geographic cloud server location design, case studies simulations fordata center energy problems, approximation algorithms and heuristics for data center energy problems,and the integration of renewable energy to cloud computing.3. Contributions to the Special IssueWorldwide there is a push to get away from traditional fossil fuel and nuclear energy sources infavor of renewables. However, electrical energy produced by both wind and solar power generation ishighly weather-dependent and weather cannot be controlled. In their contribution “Scheduling EnergyEfficient Data Centers Using Renewable Energy,” Iturriaga et al. [6] describe a multi-objective approachfor scheduling energy consumption in data centers considering traditional and green energy datasources. Two multi-objective evolutionary algorithms combined with a greedy heuristic are proposedand are enhanced by applying simulated annealing for post-hoc optimization.In “Virtual Machine Replication on Achieving Energy-Efficiency in a Cloud,” Mondal et al. [7]take on the issue of virtualization, as growth in cloud service demand has led to the establishmentof large-scale virtualized data centers in which virtual machines are used to handle user requestsfor service. To mitigate failures, replication techniques are used. The trade-offs between jobcompletion time and energy consumption in different replication schemes are characterized throughcomprehensive analytical models, which capture virtual machine state transitions and associatedpower consumption patterns.Ho et al. [8] address the issue of energy consumption from an application-level perspective intheir contribution “Characterizing Energy per Job in Cloud Applications.” They propose analyticalmodels to assess energy consumption and derive the energy per job for different configurations in datacenters. The focus is on evaluating the efficiency of applications in terms of performance and energyconsumed per job, in particular when shared resources are used and the hosts on which the virtualmachines are running are heterogeneous in terms of energy profiles, with the aim of identifying thebest combinations in the use of resources.The article “Energy Aware Pricing in a Three-Tiered Cloud Service Market,” by Paul et al. [9]discusses energy-efficient pricing strategies in the cloud service market and describes a novel theoreticalframework for implementing sustainable pricing policies and the corresponding optimal resourceprovisioning policies. They give performance evaluation with real data sets on electricity price,renewable generation, workload service request, and operational details of the data centers.4. DiscussionThe articles selected for this special issue show that data center energy efficiency has to beaddressed from various vantage points and that models need to be drawn from diverse areas. Giventhe continued impact of cloud computing globally, the topics discussed in this special issue will onlygain in importance.Acknowledgments: The work of author Wolfgang Bein was supported by the National Science Foundation grantIIA 1427584.Electronics 2018, 7, 5 3 of 3Conflicts of Interest: The author declares no conflict of interest.References1. National Science Board. Building a Sustainable Energy Future: U.S. Actions for an Effective Energy EconomyTransformation; DIANE Publishing: Collingdale, PA, USA, 2009; NSB 09-55.2. Pruhs, K. Green computing algorithmics. In Proceedings of the 2011 IEEE 52nd Annual Symposium onFoundations of Computer Science (FOCS), Palm Springs, CA, USA, 22–25 October 2011; pp. 3–4.3. Shehabi, A.; Smith, S.; Sartor, D.; Brown, R.; Herrlin, M.; Koomey, J.; Masanet, E.; Horner, N.; Azevedo, I.;Lintner, W. United States Data Center Energy Usage Report; LBNL-1005775; Lawrence Berkeley NationalLaboratory: Berkeley, CA, USA, 2016.4. Beloglazov, A.; Buyya, R.; Lee, C.L.; Zomaya, A. A Taxonomy and Survey of Energy-Efficient Data Centersand Cloud Computing Systems. Adv. Comput. 2011, 82, 47–111.5. Azimzadeh, A.; Tabrizi, N. A Taxonomy and Survey of Green Data Centers. In Proceedings of the 2015International Conference on Computational Science and Computational Intelligence (CSCI), Las Vegas, NV,USA, 7–9 December 2015; pp. 128–131.6. Iturriaga, S.; Nesmachnow, S. Scheduling Energy Efficient Data Centers Using Renewable Energy. Electronics2016, 5, 71. [CrossRef]7. Mondal, S.K.; Muppala, J.K.; Machida, F. Virtual Machine Replication on Achieving Energy-Efficiency ina Cloud. Electronics 2016, 5, 37. [CrossRef]8. Ho, T.T.N.; Gribaudo, M.; Pernici, B. Characterizing Energy per Job in Cloud Applications. Electronics 2016,5, 90. [CrossRef]9. Paul, D.; Zhong, W.-D.; Bose, S.K. Energy Aware Pricing in a Three-Tiered Cloud Service Market. Electronics2016, 5, 65. [CrossRef]© 2018 by the author. Licensee MDPI, Basel, Switzerland. This article is an open accessarticle distributed under the terms and conditions of the Creative Commons Attribution(CC BY) license (http://creativecommons.org/licenses/by/4.0/).

Energy Saving In Data Centers

Globally CO2 emissions attributable to Information Technology are on par with those resulting from aviation. Recent growth in cloud service demand has elevated energy efficiency of data centers to a critical area within green computing. Cloud computing represents a backbone of IT services and recently there has been an increase in high-definition multimedia delivery, which has placed new burdens on energy resources. Hardware innovations together with energy-efficient techniques and algorithms are key to controlling power usage in an ever-expanding IT landscape. This special issue contains a number of contributions that show that data center energy efficiency should be addressed from diverse vantage points

Wolfgang Bein

Multidisciplinary Digital Publishing Institute

Energy Saving in Data Centers

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