Skip to main content
SpringerLink
Log in

Green Software Engineering Environments

  • Chapter
Green in Software Engineering

Abstract

The term ‘software engineering environment’ (SEE) can be used to describe the network of people, software, hardware and infrastructure involved in the construction of software. In the past, research has focused primarily on the energy consumption of SEEs, including, for example, developer’s computers, networking equipment, mobile devices, and servers. In this chapter, we discuss work that has been conducted in investigating energy sinks in the SEE. This work includes existing methods, metrics and tools geared toward optimising and monitoring SEE energy consumption. However, the environmental impacts of creating software systems include more that just plug load energy consumption. The future of making SEEs ‘green’—that is, reducing their environmental and energetic footprints—relies on investigating impacts that are both indirect and direct, extend beyond just the physical development environment and are part of the entire software engineering life cycle.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 119.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. AEO2012 early release overview, Technical report. U.S. Energy Information Administration. http://www.eia.gov/forecasts/aeo/er/pdf/0383er%282012%29.pdf

  2. Agency USEP (2003) Energy star the power to protect the environment through energy efficiency. Tech. rep.

    Google Scholar 

  3. Alcott B (2005) Jevons’ paradox. Ecol Econ 54(1):9–21

    Article  Google Scholar 

  4. Amsel N, Ibrahim Z, Malik A, Tomlinson B (2011) Toward sustainable software engineering: NIER track. In: 2011 33rd international conference on software engineering (ICSE). IEEE, pp 976–979

    Google Scholar 

  5. Amsel N, Tomlinson B (2010) Green tracker: a tool for estimating the energy consumption of software. In: CHI’10 extended abstracts on human factors in computing systems. ACM, pp 3337–3342

    Google Scholar 

  6. Baer WS, Hassell S, Vollaard BA (2002) Electricity requirements for a digital society. RAND, Santa Monica, CA

    Google Scholar 

  7. Barroso LA, Hölzle U (2009) The datacenter as a computer: an introduction to the design of warehouse-scale machines. Synth Lect Comput Architect 4(1):1–108

    Article  Google Scholar 

  8. Benini L, Bogliolo A, De Micheli G (2000) A survey of design techniques for system-level dynamic power management. IEEE Trans Very Large Scale Integrat (VLSI) Syst 8(3):299–316

    Article  Google Scholar 

  9. Berl A, Gelenbe E, Di Girolamo M, Giuliani G, De Meer H, Dang MQ, Pentikousis K (2010) Energy-efficient cloud computing. Comput J 53(7):1045–1051

    Article  Google Scholar 

  10. Birol F (2010) World energy outlook. International Energy Agency

    Google Scholar 

  11. Blackburn M, Grid G (2008) Five ways to reduce data center server power consumption. Green grid

    Google Scholar 

  12. Boulding KE (1996) The economics of the coming spaceship earth. Environ Qual Growing Econ 2:3–14

    Google Scholar 

  13. Brooks FP Jr (2003) Three great challenges for half-century-old computer science. J ACM 50(1):25–26. doi:10.1145/602382.602397, URL http://doi.acm.org/10.1145/602382.602397

    Article  Google Scholar 

  14. Capra E, Formenti G, Francalanci C, Gallazzi S (2010) The impact of MIS software on it energy consumption. In: European conference of information science 2010

    Google Scholar 

  15. Capra E, Francalanci C, Slaughter SA (2012) Is software “green”? Application development environments and energy efficiency in open source applications. Inform Software Tech 54(1):60–71. doi:10.1016/j.infsof.2011.07.005, URL http://dx.doi.org/10.1016/j.infsof.2011.07.005

    Article  Google Scholar 

  16. Christensen K, Nordman B, Brown R (2004) Power management in networked devices. Computer 37(8):91–93

    Article  Google Scholar 

  17. Commission CE (2000) Energy accounting: a key tool in managing energy costs many costs. Tech. rep., California Energy Commission

    Google Scholar 

  18. Corporation I. Powertop. URL https://01.org/powertop

  19. Corporation O. The Java monitoring and management console (jconsole). URL http://openjdk.java.net/tools/svc/jconsole/

  20. Doyle MW (2005) Three pillars of the liberal peace. Am Polit Sci Rev 99(3):463–466

    Article  Google Scholar 

  21. Easton VJ, McColl JM. Statistics glossary. URL http://www.stats.gla.ac.uk/steps/glossary/timeseries.html

  22. Elliot S, Binney D (2008) Environmentally sustainable ICT: developing corporate capabilities and an industry-relevant is research agenda. In: Pacific Asia conference on information systems, Suzhou, China, 4–7 July 2008

    Google Scholar 

  23. Enterprises N. Nagios xi screenshots. URL http://www.nagios.com/products/nagiosxi/screenshots

  24. Fan X, Weber WD, Barroso LA (2007) Power provisioning for a warehouse-sized computer. ACM SIGARCH Comput Architect News 35(2):13–23

    Article  Google Scholar 

  25. Few S (2006) Information dashboard design. O’Reilly, Sebastopol, CA

    Google Scholar 

  26. Few S (2008) Time on the horizon. Vis Bus Intell Newslett 1–7

    Google Scholar 

  27. Flinn J, Satyanarayanan M (2009) Powerscope: a tool for profiling the energy usage of mobile applications. In: Proceedings. WMCSA’99. Second IEEE workshop on mobile computing systems and applications, 1999. IEEE, pp 2–10

    Google Scholar 

  28. Garrett M (2007) Powering down. Queue 5(7):16–21

    Article  MathSciNet  Google Scholar 

  29. Google: going green at Google – clean energy initiatives. URL http://www.google.com/about/datacenters/index.html

  30. Heer J, Kong N, Agrawala M (2009) Sizing the horizon: the effects of chart size and layering on the graphical perception of time series visualizations. In: Proceedings of the SIGCHI conference on human factors in computing systems. ACM, pp 1303–1312

    Google Scholar 

  31. Hewlett-Packard, Intel, Microsoft, Phoenix, Toshiba. Advanced configuration and power interface specification. URL http://www.acpi.info

  32. Hofmann M. System load indicator. URL https://launchpad.net/indicator-multiload

  33. Humble J. javasysmon. URL https://github.com/jezhumble/javasysmon

  34. IEEE Std 610.12 (1990) IEEE standard glossary of software engineering terminology

    Google Scholar 

  35. Josephsen D (2007) Building a monitoring infrastructure with Nagios. Prentice Hall PTR, Upper Saddle River, NJ

    Google Scholar 

  36. Jovanovic B, Rousseau PL (2005) General purpose technologies. Handbook Econ Growth 1:1181–1224

    Article  Google Scholar 

  37. Kansal A, Zhao F, Liu J, Kothari N, Bhattacharya AA (2010) Virtual machine power metering and provisioning. In: Proceedings of the 1st ACM symposium on cloud computing. ACM, pp 39–50

    Google Scholar 

  38. Kohlbrecher J, Hakobyan S, Pickert J, Grossmann U (2011) Visualizing energy information on mobile devices. In: 2011 IEEE 6th international conference on intelligent data acquisition and advanced computing systems (ID-AACS), vol 2. IEEE, pp 817–822

    Google Scholar 

  39. Laitner JAS, Nadel S, Elliott RN, Sachs H, Khan AS (2012) The long-term energy efficiency potential: what the evidence suggests. Tech. rep., American Council for Energy Efficiency

    Google Scholar 

  40. LeFebvre W. Unixtop. URL http://sourceforge.net/projects/unixtop/

  41. Leubner A. Usage timelines. URL http://www.refined-apps.com/trials/UsageTimelinesProrelease.apk

  42. Liu C, Qin X, Kulkarni S, Wang C, Li S, Manzanares A, Baskiyar S (2008) Distributed energy-efficient scheduling for data-intensive applications with deadline constraints on data grids. In: IEEE international performance, computing and communications conference, IPCCC 2008. IEEE, pp 26–33

    Google Scholar 

  43. Lockton D, Harrison D, Stanton NA (2012) Models of the user: designers’ perspectives on influencing sustainable behaviour. J Des Res 10(1):7–27

    Google Scholar 

  44. Lovins AB (2011) Re: The efficiency dilemma. The Mail, The New Yorker

    Google Scholar 

  45. Mahesri A, Vardhan V (2005) Power consumption breakdown on a modern laptop. In: Power-aware computer systems. Springer, pp 165–180

    Google Scholar 

  46. Mersenne Research I. The great Internet Mersenne prime search. URL http://www.mersenne.org/freesoft/

  47. Mingay S (2007) Green IT: the new industry shock wave. Gartner RAS Research Note G 153703

    Google Scholar 

  48. Mitchell-Jackson JD (2001) Energy needs in an internet economy: a closer look at data centers. Ph.D. thesis, University of California

    Google Scholar 

  49. Mittal R, Kansal A, Chandra R (2012) Empowering developers to estimate app energy consumption. In: Proceedings of the 18th annual international conference on mobile computing and networking. ACM, pp 317–328

    Google Scholar 

  50. Murugesan S (2008) Harnessing Green IT: principles and practices. IT Prof 10(1):24–33

    Article  Google Scholar 

  51. Naumann S, Dick M, Kern E, Johann T (2011) The GREENSOFT model: a reference model for green and sustainable software and its engineering. Sustain Comput Informat Syst 1(4):294–304, http://dx.doi.org/10.1016/j.suscom.2011.06.004. URL http://www.sciencedirect.com/science/article/pii/S2210537911000473

    Article  Google Scholar 

  52. Odessa: sample computer network diagrams. URL http://www.conceptdraw.com/samples/network-diagram

  53. Owen D (2010) The efficiency dilemma. Annals of environmentalism, The New Yorker

    Google Scholar 

  54. Penzenstadler B, Raturi A, Richardson D, Tomlinson B (2014) Safety, security, now sustainability: the non-functional requirement for the 21st century. In: Software (IEEE) Vol. 31 (3)

    Google Scholar 

  55. Rawson A, Pfleuger J, Cader T (2008) Green grid data center power efficiency metrics: PUE and DCIE. The green grid white paper 6

    Google Scholar 

  56. Research M. Joulemeter: Computational energy measurement and optimization. URL http://research.microsoft.com/en-us/projects/joulemeter/default.aspx

  57. Rosseto EP (2011) Study of the correlation between software developer profile and code efficiency. Ph.D. thesis, Politecnico di Milano, Milan

    Google Scholar 

  58. Sanchez MC, Brown RE, Webber C, Homan GK (2008) Savings estimates for the United States Environmental Protection Agency’s energy star voluntary product labeling program. Energy Policy 36(6):2098–2108

    Article  Google Scholar 

  59. Shah A, Christian T, Patel CD, Bash C, Sharma RK (2009) Assessing ICT’s environmental impact. IEEE Comput 42(7):91–93

    Article  Google Scholar 

  60. Smith JW (2010) Green cloud a literature review of energy-aware computing. Ph.D. thesis, University of St. Andrews, Fife

    Google Scholar 

  61. Thomas I, Nejmeh BA (1992) Definitions of tool integration for environments. IEEE Software 9(2):29–35, http://doi.ieeecomputersociety.org/10.1109/52.120599

    Article  Google Scholar 

  62. Tomlinson B (2010) Greening through IT. MIT Press, Cambridge, MA

    Google Scholar 

  63. Tomlinson B, Silberman MS, White J (2011) Can more efficient it be worse for the environment? Computer 44(1):87–89

    Article  Google Scholar 

  64. Tufte ER (2006) Beautiful evidence, vol 23. Graphics Press, Cheshire, CT

    Google Scholar 

  65. Webb M et al (2008) Smart 2020. Enabling the low carbon economy in the information age. The Climate Group. London 1(1), 1–1

    Google Scholar 

Download references

Acknowledgement

We would like to thank Birgit Penzenstadler and Sunny Karnani for their feedback on the chapter. We would also like to thank Taylor Kisor-Smith for his contributions to the Joulery prototype.

Author information

Authors and Affiliations

  1. University of California, Irvine, Irvine, CA, USA

    Ankita Raturi, Bill Tomlinson & Debra Richardson

Authors
  1. Ankita Raturi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bill Tomlinson
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Debra Richardson
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ankita Raturi .

Editor information

Editors and Affiliations

  1. Department of Information Technologies and Systems, University of Castilla-La Mancha, Ciudad Real, Spain

    Coral Calero

  2. Department of Information Technologies and Systems, University of Castilla-La Mancha, Ciudad Real, Spain

    Mario Piattini

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Raturi, A., Tomlinson, B., Richardson, D. (2015). Green Software Engineering Environments. In: Calero, C., Piattini, M. (eds) Green in Software Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-08581-4_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-08581-4_2

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08580-7

  • Online ISBN: 978-3-319-08581-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation