skip to main content
10.1145/2598394.2605695acmconferencesArticle/Chapter ViewAbstractPublication PagesgeccoConference Proceedingsconference-collections
technical-note

A survey on sustainability in ICT: a computing perspective

Published:12 July 2014Publication History

ABSTRACT

The rise of the data centers industry, together with the emergence of large cloud computing that require large quantities of resources to be maintained, brought the need of providing a sustainable development process. Through this paper we aim to provide an introductory insight on the status and tools available to tackle this perspective within the evolutionary and genetic algorithms community. Existing advancements are also emphasized and perspectives outlined.

References

  1. Open Networking Foundation. http://www.opennetworking.org.Google ScholarGoogle Scholar
  2. AMD. Cool'n'Quiet Technology. http://www.amd.com/us/products/technologies/cool-n-quiet/Pages/cool-n-q%uiet.aspx, 2004.Google ScholarGoogle Scholar
  3. Janet Anders, Saroosh Shabbir, Stefanie Hilt, and Eric Lutz. Landauer's Principle in the Quantum Domain. In Cooper et al. {17}, pages 13--18.Google ScholarGoogle Scholar
  4. John Pflueger Andy Rawson and Tahir Cader. The Green Grid Data Center Power Efficiency Metrics: PUE and DCiE. http://www.thegreengrid.org/Global/Content/white-papers/The-Green-Grid-Data-Center-Power-Efficiency-Metrics-PUE-and-DCiE#sthash.tnUhZM7e.dpuf, Oct. 2007.Google ScholarGoogle Scholar
  5. Michael Armbrust, Armando Fox, Rean Griffith, Anthony D. Joseph, Randy Katz, Andy Konwinski, Gunho Lee, David Patterson, Ariel Rabkin, Ion Stoica, and Matei Zaharia. A View of Cloud Computing. Commun. ACM, 53(4):50--58, April 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Marko Bajec and Johann Eder, editors. Advanced Information Systems Engineering Workshops - CAiSE 2012 International Workshops, Gdask, Poland, June 25-26, 2012. Proceedings, volume 112 of Lecture Notes in Business Information Processing. Springer, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Anton Beloglazov, Jemal Abawajy, and Rajkumar Buyya. Energy-Aware Resource Allocation Heuristics for Efficient Management of Data Centers for Cloud Computing. Future Generation Computer Systems, 28(5):755--768, 2012. Special Section: Energy efficiency in large-scale distributed systems. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Anton Beloglazov, Rajkumar Buyya, Young Choon Lee, and Albert Y. Zomaya. A Taxonomy and Survey of Energy-Efficient Data Centers and Cloud Computing Systems. CoRR, abs/1007.0066, 2010.Google ScholarGoogle Scholar
  9. S. Benedict, R. S. Rejitha, and C. B. Bright. Energy Consumption-Based Performance Tuning of Software and Applications Using Particle Swarm Optimization. In Software Engineering (CONSEG), 2012 CSI Sixth International Conference on, pages 1--6, sept. 2012.Google ScholarGoogle ScholarCross RefCross Ref
  10. C. H. Bennett. Logical Reversibility of Computation. IBM J. Res. Dev., 17(6):525--532, November 1973. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Andreas Berl, Erol Gelenbe, Marco Di Girolamo, Giovanni Giuliani, Hermann De Meer, Minh Quan Dang, and Kostas Pentikousis. Energy-Efficient Cloud Computing. Comput. J., 53(7):1045--1051, September 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Antoine Bérut, Artak Arakelyan, Artyom Petrosyan, Sergio Ciliberto, Raoul Dillenschneider, and Eric Lutz. Experimental verification of Landauer's principle linking information and thermodynamics. Nature, 483(7388):187--189, Mar 2012.Google ScholarGoogle ScholarCross RefCross Ref
  13. Rajkumar Buyya, Rajiv Ranjan, and Rodrigo N. Calheiros. InterCloud: Utility-Oriented Federation of Cloud Computing Environments for Scaling of Application Services. In Ching-Hsien Hsu, Laurence T. Yang, Jong Hyuk Park, and Sang-Soo Yeo, editors, Algorithms and Architectures for Parallel Processing, volume 6081 of Lecture Notes in Computer Science, pages 13--31. Springer Berlin Heidelberg, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Ying Chang-tian and Yu Jiong. Energy-Aware Genetic Algorithms for Task Scheduling in Cloud Computing. In China Grid Annual Conference (ChinaGrid), 2012 Seventh, pages 43--48, sept. 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. J. Clidaras, D. W. Stiver, and W. Hamburgen. Water-based Data Center. http://www.google.com/patents/US7525207, April 28 2009. US Patent 7,525,207.Google ScholarGoogle Scholar
  16. Computer & Communications Industry Association. Cloud Computing. http://www.ccianet.org/wp-content/uploads/library/Cloud_Computing.pdf, 2009.Google ScholarGoogle Scholar
  17. S. Barry Cooper, Prakash Panangaden, and Elham Kashefi, editors. Proceedings Sixth Workshop on Developments in Computational Models: Causality, Computation, and Physics, DCM 2010, Edinburgh, Scotland, 9-10th July 2010, volume 26 of EPTCS, 2010.Google ScholarGoogle Scholar
  18. M. P. Czamara and O. P. Morales. Compressed Air Cooling System for Data Center. https://www.google.com/patents/EP2554032A1?cl=en, February 6 2013. EP Patent App. EP20,110,712,079.Google ScholarGoogle Scholar
  19. Kristof Du Bois, Tim Schaeps, Stijn Polfliet, Frederick Ryckbosch, and Lieven Eeckhout. SWEEP: Evaluating Computer System Energy Efficiency Using Synthetic Workloads. In Proceedings of the 6th International Conference on High Performance and Embedded Architectures and Compilers, HiPEAC '11, pages 159--166, New York, NY, USA, 2011. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Embedded Microprocessor Benchmark Consortium (EEMBC). Energybench V1.0 Power/Energy Benchmarks. http://www.eembc.org/benchmark/power_sl.php.Google ScholarGoogle Scholar
  21. Eugen Feller, Louis Rilling, and Christine Morin. Energy-Aware Ant Colony Based Workload Placement in Clouds. In Proceedings of the 2011 IEEE/ACM 12th International Conference on Grid Computing, GRID '11, pages 26--33, Washington, DC, USA, 2011. IEEE Computer Society. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Ian Foster, Yong Zhao, Ioan Raicu, and Shiyong Lu. Cloud Computing and Grid Computing 360-Degree Compared. 2008 Grid Computing Environments Workshop, abs/0901.0(5):1--10, 2008.Google ScholarGoogle ScholarCross RefCross Ref
  23. Siddharth Garg, Diana Marculescu, Radu Marculescu, and Umit Ogras. Technology-driven Limits on DVFS Controllability of Multiple Voltage-frequency Island Designs: A System-level Perspective. In Proceedings of the 46th Annual Design Automation Conference, DAC '09, pages 818--821, New York, NY, USA, 2009. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Greenpeace International Gary Cook. How Green is Your Cloud? Catalysing an Energy Revolution. http://www.greenpeace.org/new-zealand/Global/international/publications/climate/2012/iCoal/HowCleanisYourCloud.pdf, apr 2012.Google ScholarGoogle Scholar
  25. Google. Efficiency: How we do it. http://www.google.com/about/datacenters/efficiency/internal/index.html#measuring-efficiency.Google ScholarGoogle Scholar
  26. Hadi Goudarzi, Mohammad Ghasemazar, and Massoud Pedram. SLA-based optimization of power and migration cost in cloud computing. In Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012), CCGRID '12, pages 172--179, Washington, DC, USA, 2012. IEEE Computer Society. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. June A. Grant. Implementing Sustainable Practices @ NASA Ames, GreenGov Symposium, 2011 Washington, USA. http://www.greengov2011.org/presentations/GreenFacilities/GreenGov-2011-GreenFacilities-S5-JuneGrant.pdf, Oct 2011.Google ScholarGoogle Scholar
  28. Albert G. Greenberg and Kazem Sohraby, editors. Proceedings of the IEEE INFOCOM 2012, Orlando, FL, USA, March 25-30, 2012. IEEE, 2012.Google ScholarGoogle Scholar
  29. Katherine Griffiths. World's greenest office block set for Paris, The Telegraph. http://www.telegraph.co.uk/finance/newsbysector/constructionandproperty/2781961/Worlds-greenest-office-block-set-for-Paris.html, Jan 2008.Google ScholarGoogle Scholar
  30. M. N. Halgamuge, S. M. Guru, and A. Jennings. Energy Efficient Cluster Formation in Wireless Sensor Networks. In Telecommunications, 2003. ICT 2003. 10th International Conference on, volume 2, pages 1571--1576 vol. 2, Feb 2003.Google ScholarGoogle ScholarCross RefCross Ref
  31. Haitham Hassanieh, Piotr Indyk, Dina Katabi, and Eric Price. Nearly Optimal Sparse Fourier Transform. In Proceedings of the Forty-fourth Annual ACM Symposium on Theory of Computing, STOC '12, pages 563--578, New York, NY, USA, 2012. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Intel White Paper 30057701. Wireless Intel SpeedStep power manager: optimizing power consumption for the Intel PXA27x processor family. Technical report, Intel, 2004.Google ScholarGoogle Scholar
  33. Jeremy Kirk, IDG News Service, PCWorld. HP Opens First Ever Wind-cooled Data Center. http://www.pcworld.com/article/188996/hp_opens_first_ever_wind_cooled_data_center.html, 2010.Google ScholarGoogle Scholar
  34. Ajay M. Joshi, Lieven Eeckhout, Lizy Kurian John, and Ciji Isen. Automated Microprocessor Stressmark Generation. In HPCA, pages 229--239. IEEE Computer Society, 2008.Google ScholarGoogle ScholarCross RefCross Ref
  35. Jonathan G. Koomey. Worldwide Electricity Used in Data Centers. Environmental Research Letters, 3(3):034008, 2008.Google ScholarGoogle ScholarCross RefCross Ref
  36. Jonathan G. Koomey, Stephen Berard, Marla Sanchez, and Henry Wong. Implications of Historical Trends in the Electrical Efficiency of Computing. IEEE Annals of the History of Computing, 33(3):46--54, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. K. Kumar and Yung-Hsiang Lu. Cloud Computing for Mobile Users: Can Offloading Computation Save Energy? Computer, 43(4):51--56, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. R. Landauer. Irreversibility and Heat Generation in the Computing Process. IBM J. Res. Dev., 5(3):183--191, Jul 1961. Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. Klaus-Dieter Lange. Identifying Shades of Green: The SPECpower Benchmarks. IEEE Computer, 42(3):95--97, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. James Laudon. Performance/Watt: The New Server Focus. SIGARCH Comput. Archit. News, 33(4):5--13, November 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  41. Wei-Ru Lee, Hung-Yi Teng, and Ren-Hung Hwang. Optimization of Cloud Resource Subscription Policy. In Cloud Computing Technology and Science (CloudCom), 2012 IEEE 4th International Conference on, pages 449--455, dec. 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  42. Bo Li, Jianxin Li, Jinpeng Huai, Tianyu Wo, Qin Li, and Liang Zhong. EnaCloud: An Energy-Saving Application Live Placement Approach for Cloud Computing Environments. In Cloud Computing, 2009. CLOUD '09. IEEE International Conference on, pages 17--24, Sept 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  43. Dawei Li and Jie Wu. Energy-aware Scheduling on Multiprocessor Platforms. Springer Publishing Company, Incorporated, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. G. Li, M. Li, S. Azarm, J. Rambo, and Y. Joshi. Optimizing Thermal Design of Data Center Cabinets with a New Multi-objective Genetic Algorithm. Distrib. Parallel Databases, 21(2-3):167--192, June 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  45. Qiang Li. Applying Stochastic Integer Programming to Optimization of Resource Scheduling in Cloud Computing. JNW, 7(7):1078--1084, 2012.Google ScholarGoogle Scholar
  46. Siva Theja Maguluri, R. Srikant, and Lei Ying. Stochastic Models of Load Balancing and Scheduling in Cloud Computing Clusters. In Greenberg and Sohraby {28}, pages 702--710.Google ScholarGoogle Scholar
  47. Mark Gregory, BBC News. Inside Facebook's Green and Clean Arctic Data Centre. http://www.bbc.com/news/business-22879160, 2013.Google ScholarGoogle Scholar
  48. Paul A. Mathew, Srirupa Ganguly, Steve E. Greenberg, and Dale A. Sartor. Self-benchmarking Guide for Data Centers: Metrics, Benchmarks, Actions. Technical report, Lawrence Berkeley National Laboratory, Jul 2009.Google ScholarGoogle Scholar
  49. Sara McAllister, Van P. Carey, Amip Shah, Cullen Bash, and Chandrakant D. Patel. Strategies for Effective use of Energy-based Modeling of Data Center Thermal Management Systems. Microelectronics Journal, 39(7):1023--1029, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  50. Nick McKeown, Tom Anderson, Hari Balakrishnan, Guru Parulkar, Larry Peterson, Jennifer Rexford, Scott Shenker, and Jonathan Turner. OpenFlow: enabling innovation in campus networks. In Proc. of the ACM SIGCOMM 2008 conference, pages 38(2):69--74, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  51. M. Mezmaz, N. Melab, Y. Kessaci, Y. C. Lee, E. G. Talbi, A. Y. Zomaya, and D. Tuyttens. A Parallel Bi-Objective Hybrid Metaheuristic for Energy-Aware Scheduling for Cloud Computing Systems. J. Parallel Distrib. Comput., 71(11):1497--1508, November 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  52. G. E. Moore. Cramming More Components onto Integrated Circuits. Electronics, 38(8):114--117, Apr 1965.Google ScholarGoogle Scholar
  53. Samuel K. Moore. Landauer Limit Demonstrated, IEEE Spectrum. http://spectrum.ieee.org/computing/hardware/landauer-limit-demonstrated, Mar 2012.Google ScholarGoogle Scholar
  54. The Green Grid Global Harmonization of Data Center Efficiency Metrics Task Force. Harmonizing Global Metrics for Data Center Energy Efficiency, March 2014.Google ScholarGoogle Scholar
  55. Open Networking Foundation. SDN architecture overview. ONF White paper, Dec. 2013.Google ScholarGoogle Scholar
  56. Parliament Office of Science and Technology. ICT and CO2 Emissions. http://www.parliament.uk/documents/post/postpn319.pdf, Dec 2008.Google ScholarGoogle Scholar
  57. C. D. Patel, C. E. Bash, and A. H. Beitelmal. Smart Cooling of Data Centers. https://www.google.com/patents/US6574104, June 3 2003. US Patent 6,574,104.Google ScholarGoogle Scholar
  58. Dung H. Phan, Junichi Suzuki, Raymond Carroll, Sasitharan Balasubramaniam, William Donnelly, and Dmitri Botvich. Evolutionary Multiobjective Optimization for Green Clouds. In Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference companion, GECCO Companion '12, pages 19--26, New York, NY, USA, 2012. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  59. J. J. Prevost, K. Nagothu, B. Kelley, and M. Jamshidi. Prediction of Cloud Data Center Networks Loads using Stochastic and Neural Models. In System of Systems Engineering (SoSE), 2011 6th International Conference on, pages 276--281, june 2011.Google ScholarGoogle ScholarCross RefCross Ref
  60. Paul Rad, Max Thoene, and Tim Webb. Best Practices for Increasing Data Center Energy Efficiency, February 2008.Google ScholarGoogle Scholar
  61. Jeffrey Rambo and Yogendra Joshi. Modeling of Data Center Airflow and Heat Transfer: State of the Art and Future Trends. Distributed and Parallel Databases, 21(2-3):193--225, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  62. Suzanne Rivoire, Mehul A. Shah, Parthasarathy Ranganathan, and Christos Kozyrakis. JouleSort: A Balanced Energy-efficiency Benchmark. In Proceedings of the 2007 ACM SIGMOD International Conference on Management of Data, SIGMOD '07, pages 365--376, New York, NY, USA, 2007. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  63. Victor Romanov, Aleksandra Varfolomeeva, and Andrey Koryakovskiy. Branching Processes Theory Application for Cloud Computing Demand Modeling Based on Traffic Prediction. In Bajec and Eder {6}, pages 502--510.Google ScholarGoogle Scholar
  64. Richard Sawyer. Calculating Total Power Requirements for Data Centers, 2011.Google ScholarGoogle Scholar
  65. Storage Networking Industry Association (SNIA). Storage Management Initiative Specification. http://snia.org/tech_activities/publicreview, 2013.Google ScholarGoogle Scholar
  66. S. Subashini and V. Kavitha. A Survey on Security Issues in Service Delivery Models of Cloud Computing. Journal of Network and Computer Applications, 34(1):1--11, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  67. Q. Tang, S. K. S. Gupta, and G. Varsamopoulos. Energy-Efficient Thermal-Aware Task Scheduling for Homogeneous High-Performance Computing Data Centers: A Cyber-Physical Approach. Parallel and Distributed Systems, IEEE Transactions on, 19(11):1458--1472, Nov 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  68. A.-A. Tantar, Anh Quan Nguyen, P. Bouvry, B. Dorronsoro, and E.-G. Talbi. Computational Intelligence for Cloud Management Current Trends and Opportunities. In Evolutionary Computation (CEC), 2013 IEEE Congress on, pages 1286--1293, June 2013.Google ScholarGoogle ScholarCross RefCross Ref
  69. Alexandru-Adrian Tantar, Grégoire Danoy, Pascal Bouvry, and SameeU. Khan. Energy-Efficient Computing Using Agent-Based Multi-objective Dynamic Optimization. In Jae H. Kim and Myung J. Lee, editors, Green IT: Technologies and Applications, pages 267--287. Springer Berlin Heidelberg, 2011.Google ScholarGoogle ScholarCross RefCross Ref
  70. Alexandru-Adrian Tantar, Emilia Tantar, and Pascal Bouvry. A Classification of Dynamic Multi-objective Optimization Problems. In Proceedings of the 13th Annual Conference Companion on Genetic and Evolutionary Computation, GECCO '11, pages 105--106, New York, NY, USA, 2011. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  71. E. Tantar, A. Tantar, and P. Bouvry. On Dynamic Multi-Objective Optimization, Classification and Performance Measures. In Evolutionary Computation (CEC), 2011 IEEE Congress on, pages 2759--2766, June 2011.Google ScholarGoogle ScholarCross RefCross Ref
  72. Lizhe Wang and SameeU. Khan. Review of Performance Metrics for Green Data Centers: A Taxonomy Study. The Journal of Supercomputing, 63(3):639--656, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  73. White Paper, Google. Google's Carbon Offsets: Collaboration and Due Diligence. https://static.googleusercontent.com/media/www.google.com/en//green/pdfs/google-carbon-offsets.pdf, 2011.Google ScholarGoogle Scholar
  74. Erik Young, Paul Cao, and Mike Nikolaiev. First TPC-Energy Benchmark: Lessons Learned in Practice. In Raghunath Nambiar and Meikel Poess, editors, Performance Evaluation, Measurement and Characterization of Complex Systems, volume 6417 of Lecture Notes in Computer Science, pages 136--152. Springer Berlin Heidelberg, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  75. Qi Zhang, Lu Cheng, and Raouf Boutaba. Cloud Computing: State-Of-The-Art and Research Challenges. Journal of Internet Services and Applications, 1:7--18, 2010.Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. A survey on sustainability in ICT: a computing perspective

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Conferences
      GECCO Comp '14: Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation
      July 2014
      1524 pages
      ISBN:9781450328814
      DOI:10.1145/2598394

      Copyright © 2014 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 12 July 2014

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • technical-note

      Acceptance Rates

      GECCO Comp '14 Paper Acceptance Rate180of544submissions,33%Overall Acceptance Rate1,669of4,410submissions,38%

      Upcoming Conference

      GECCO '24
      Genetic and Evolutionary Computation Conference
      July 14 - 18, 2024
      Melbourne , VIC , Australia

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader