Skip to main content

Energy Cost-Effectiveness of Cloud Service Datacenters

  • Conference paper
  • 1278 Accesses

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 223))

Abstract

Cloud computing is a computation intensive service that clusters distributed computers providing applications as services and on-demand resources over Internet. Theoretically, such consolidated resource enhances the energy efficiency of both clients and servers. In reality, cloud computing is a panacea for enhancing energy efficiency under some certain conditions. For a user of cloud services, the computing resources are located at remote machines. Pioneers in exploring cloud computing, such as Google, AmazonWeb, Microsoft Azure, Yahoo, and IBM all use web pages as service interface via HTTP protocol. Through appropriated designs, sorting, one of the most frequently used algorithms, required by a web page can be executed and succeed by either clients or servers. As the model proposed in this paper, such client-server balanced computing allocation suggests a more energy-efficient and cost-effective web service.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Forrester research - marketing and strategy data (2008), http://www.forrester.com/consumerdata/overview

  2. Internet world stats - world internet users and population stats (2010), http://internetworldstats.com/stats.htm

  3. Nuclear energy institute - u.s. nuclear power plants (2011), http://www.nei.org/resourcesandstats/nuclear_statistics

  4. Ayala, J.L., Veidenbaum, A., Lpez-Vallejo, M.: Power-aware compilation for register file energy reduction. International Journal of Parallel Programming 31, 451–467 (2003), http://dx.doi.org/10.1023/B:IJPP.0000004510.66751.2e , doi:10.1023/B:IJPP.0000004510.66751.2e

    Article  Google Scholar 

  5. Barroso, L.A., Hölzle, U.: The case for energy-proportional computing. IEEE Computer 40(12), 33–37 (2007), http://doi.ieeecomputersociety.org/10.1109/MC.2007.443

    Article  Google Scholar 

  6. Berl, A., Gelenbe, E., Di Girolamo, M., Giuliani, G., De Meer, H., Dang, M., Pentikousis, K.: Energy-efficient cloud computing. The Computer Journal 53(7), 1045 (2010)

    Article  Google Scholar 

  7. Bianchini, R., Rajamony, R.: Power and energy management for server systems. Computer 37(11), 68–76 (2004)

    Article  Google Scholar 

  8. Bunse, C., Höpfner, H., Roychoudhury, S., Mansour, E.: Choosing the best sorting algorithm for optimal energy consumption? In: Proceedings of the International Conference on Software and Data Technologies (ICSOFT), pp. 199–206 (2009)

    Google Scholar 

  9. Elnozahy, E., Kistler, M., Rajamony, R.: Energy-efficient server clusters. Power-Aware Computer Systems, 179–197 (2003)

    Google Scholar 

  10. Hamilton, J.: Cooperative expendable micro-slice servers (CEMS): low cost, low power servers for internet-scale services. In: Conference on Innovative Data Systems Research (CIDR 2009), Citeseer (January 2009)

    Google Scholar 

  11. Knuth, D.E.: The Art of Computer Programming, Sorting and Searching, 2nd edn., vol. 3. Addison-Wesley, Reading (1998)

    MATH  Google Scholar 

  12. Rusu, C., Ferreira, A., Scordino, C., Watson, A.: Energy-efficient real-time heterogeneous server clusters. In: Proceedings of the 12th IEEE Real-Time and Embedded Technology and Applications Symposium, pp. 418–428. IEEE, Los Alamitos (2006)

    Google Scholar 

  13. Schmidt, D., Wehn, N.: Dram power management and energy consumption: a critical assessment. In: Proceedings of the 22nd Annual Symposium on Integrated Circuits and System Design: Chip on the Dunes, SBCCI 2009, pp. 32:1–32:5. ACM, New York (2009), http://doi.acm.org/10.1145/1601896.1601937

    Google Scholar 

  14. Siegmund, N., Rosenmüller, M., Apel, S.: Automating energy optimization with features. In: Proceedings of the 2nd International Workshop on Feature-Oriented Software Development, FOSD 2010, pp. 2–9. ACM, New York (2010), http://doi.acm.org/10.1145/1868688.1868690

    Google Scholar 

  15. Skiena, S.S.: The Algorithm Design Manual, 2nd edn. Springer, Heidelberg (2008)

    Book  MATH  Google Scholar 

  16. Zedlewski, J., Sobti, S., Garg, N., Zheng, F., Krishnamurthy, A., Wang, R.: Modeling hard-disk power consumption. In: Proceedings of the 2nd USENIX Conference on File and Storage Technologies, pp. 217–230. USENIX Association (2003)

    Google Scholar 

  17. Zhong, S., Shen, Y., Hao, F.: Tuning compiler optimization options via simulated annealing. In: Second International Conference on Future Information Technology and Management Engineering, FITME 2009, pp. 305–308 (2009)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Tang, CJ., Dai, MR. (2011). Energy Cost-Effectiveness of Cloud Service Datacenters. In: Chang, RS., Kim, Th., Peng, SL. (eds) Security-Enriched Urban Computing and Smart Grid. SUComS 2011. Communications in Computer and Information Science, vol 223. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23948-9_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-23948-9_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23947-2

  • Online ISBN: 978-3-642-23948-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics