Review of Industrial Organization

, Volume 38, Issue 4, pp 405–421

Cloud Computing: Architectural and Policy Implications

Article

Abstract

Cloud computing has emerged as perhaps the hottest development in information technology. Despite all of the attention it has garnered, existing analyses focus almost exclusively on the issues surrounding data privacy without exploring cloud computing’s architectural and policy implications. This Article offers an initial exploratory analysis in that direction. It begins by introducing key cloud computing concepts, such as service oriented architectures, thin clients, and virtualization, and discusses the leading delivery models and deployment strategies being pursued by cloud computing providers. It then analyzes the economics of cloud computing in terms of reducing costs, transforming capital expenditures into operating expenditures, aggregating demand, increasing reliability, and reducing latency. It then discusses the architectural implications of cloud computing for access networking (focusing on bandwidth, reliability, quality of service, and ubiquity) and data center interconnectivity (focusing on bandwidth, reliability, security and privacy, control over routing policies, standardization, and metering and payment). It closes by offering a few observations on the impact of cloud computing on the industry structure for data centers, server-related technologies, router-based technologies, and access networks, as well as its implications for regulation.

Keywords

Service oriented architectures Virtualization Data centers Privacy Hypervisors 

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References

  1. Birman, K., Chockler, G., & van Renesse, R. (2008). Towards a cloud computing research agenda, http://www.cs.cornell.edu/projects/quicksilver/public_pdfs/SIGACT2.pdf.
  2. Brodkin, J. (2010, June 10). Amazon cloud uses FedEx instead of the Internet to ship data, Network World, http://www.networkworld.com/news/2010/061010-amazon-cloud-fedex.html.
  3. Buyya R., Yeo C., Venugopal S., Broberg J., Brandic I. (2009) Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility. Future Generation Computer Systems 25: 599–616CrossRefGoogle Scholar
  4. Carr N. (2008) The big switch. W.W. Norton, New YorkGoogle Scholar
  5. Foster, I., Zhao, Y., Raicu, I., & Lu, S. (2008). Cloud computing and grid computing 360-degree compared. In Proceedings grid computing environments workshop: GCE 2008 (pp. 1–10). doi:10.1109/GCE.2008.4738445.
  6. Geelan, J. (2009, January 24). Twenty one experts define cloud computing. Cloud Computing Journal. http://www.cloudcomputing.sys-con.com/node/612375.
  7. Johnson, B. (2008, September 29). Cloud computing is a trap, warns GNU founder Richard Stallman. http://www.guardian.co.uk/technology/2008/sep/29/cloud.computing.richard.stallman.
  8. Mell, P. & Grance, T. (2009, October 7). The NIST definition of cloud computing (version 15). http://www.csrc.nist.gov/groups/SNS/cloud-computing/cloud-def-v15.doc.
  9. Schmalensee R. (1984) Gaussian demand and commodity pricing. Journal of Business 57: S211–S230CrossRefGoogle Scholar
  10. Vaquero L., Rodero-Merino L., Caceres J, Lindner M. (2009) A break in the clouds: Toward a cloud definition. ACM SIGCOMM Computer Communication Review 39: 50–55CrossRefGoogle Scholar
  11. Weinhardt, C., Anandasivam, A., Blau, & Stösser, J. (2009). Business models in the service world (pp. 28–33). IT Pro.Google Scholar
  12. Weinman, J. (2008, September 7). The 10 Laws of Cloudonomics. GigaOm, http://www.gigaom.com/2008/09/07/the-10-laws-of-cloudonomics/.
  13. Weinman, J. (2009, November 30). Mathematical proof of the inevitability of cloud computing. http://www.cloudonomics.wordpress.com/2009/11/30/mathematical-proof-of-the-inevitability-of-cloudcomputing/.
  14. Weinman, J. (2011a, February 27). Smooth operator: The value of demand aggregation. http://www.joeweinman.com/Resources/Joe/Weinman_Smooth-Operator_Demand_Aggregation.pdf.
  15. Weinman, J. (2011b, April 12). As time goes by: The law of could response time, http://www.joeweinman.com/Resources/Joe_Weinman_As_Time_Goes_By.pdf.
  16. Yoo C. (2010a) Innovations in the Internet’s architecture that challenge the status quo. Journal on Telecommunications and High Technology Law 8: 79–99Google Scholar
  17. Yoo C. (2010b) The changing patterns of internet usage. Federal Communications Law Journal 63: 67–89Google Scholar

Copyright information

© Springer Science+Business Media, LLC. 2011

Authors and Affiliations

  1. 1.University of PennsylvaniaPhiladelphiaUSA

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