Abstract
Cloud computing, as an innovative business model, has experienced rapid diffusion across the international business world, offering many benefits to both the demand and the supply side of the ICT market. In particular, the public cloud approach receives more attention and the Infrastructure as a Service (IaaS) model is expected to be the fastest growing model of public cloud computing, as it is considered to be a very good solution for companies needing the control of fundamental computing resources, such as memory, computing power and storage capacity. Currently, the battle for a dominant market share grows the competition among cloud providers and leads to the development of new pricing schemes, in order to meet the market demand. However, the choice of the cheapest cloud hosting provider depends exclusively on the clients’ needs and this is why prices for cloud services are a result of a multidimensional function shaped by the service’s characteristics. Into that context, this paper summarizes the findings of an initial work on the construction of a price index based on a hedonic pricing method, taking into account different factors of IaaS cloud computing services, including two of the most important players in the cloud market, Google and Microsoft Azure. The aim of this study is to provide price indices both on a continent level and globally, in an effort to investigate differences in pricing policies in different marketplaces. Comparing the results leads to important conclusions related to pricing policies of IaaS cloud services.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Etro F (2009) The economic impact of cloud computing on business creation, employment and output in Europe. Rev Bus Econ 54(2):179–208
Mell P, Grance T (2011) The NIST definition of cloud computing. NIST special publication 800(145):7
Anderson E, Eschinger C, Wurster L, de Silva F, Contu R, Liu V, Biscotti F, Petri G, Zhang J, Yeates M (2013) Forecast overview: public cloud services, worldwide, 2011–2016, 4Q12 Update, Market analysis and statistics. Gartner Group, Inc., Connecticut, USA
Hurwitz J, Kaufman M, Halper DF (2012) Cloud services for dummies. IBM Limited Edition. Wiley, New York
Vinu Prasad G, Rao S, Prasad AS (2012) A combinatorial auction mechanism for multiple resource procurement in cloud computing. In: 12th International conference on intelligent systems design and applications (ISDA). IEEE, pp 337–344
Siham EK, Schlereth C, Skiera B (2012) Price comparison for infrastructure-as-a-service. ECIS (p. 61):12
Martens B, Walterbusch M, Teuteberg F (2012) Costing of cloud computing services: a total cost of ownership approach. In: 45th Hawaii international conference onsystem science (HICSS), 2012. IEEE, pp 1563–1572
Andra RS (2013) Investigating pricing and negotiation models for cloud computing. MSc in High Performance, Computing University of Edinburgh:81
Mitropoulou P, Filiopoulou E, Tsaroucha S, Michalakelis C, Nikolaidou M (2015) A hedonic price index for cloud computing services. In: CLOSER 2015, 5th international conference on cloud computing and services science, Lisbon, Portugal, 20–22 May 2015
Sharma B, Thulasiram RK, Thulasiraman P, Buyya R (2015) Clabacus: a risk-adjusted cloud resources pricing model using financial option theory. IEEE Trans Cloud Comput 3(3):332–344
Grivas SG, Kumar TU, Wache H (2010) Cloud broker: bringing intelligence into the cloud. In: 2010 IEEE 3rd international conference on cloud computing (CLOUD), 2010. IEEE, pp 544–545
Petri I, Diaz-Montes J, Zou M, Beach T, Rana O, Parashar M (2015) Market models for federated clouds. IEEE Trans Cloud Comput 3(3):398–410. doi:10.1109/TCC.2015.2415792
Rogers O, Cliff D (2012) A financial brokerage model for cloud computing. J Cloud Comput 1(1):1–12
Grossman RL (2009) The case for cloud computing. IT Prof 11(2):23–27
Clamp P, Cartlidge J (2013) Pricing the cloud: an adaptive brokerage for cloud computing. In: 5th International conference on advances in system simulation (SIMUL-2013). IARIA XPS Press, Venice, Citeseer, pp 113–121
Al-Roomi M, Al-Ebrahim S, Buqrais S, Ahmad I (2013) Cloud computing pricing models: a survey. Int J Grid Distributed Comput 6(5):93–106
Mihailescu M, Teo YM (2010) Dynamic resource pricing on federated clouds. In: 2010 10th IEEE/ACM international conference on cluster, cloud and grid computing (CCGrid), 2010. IEEE, pp 513–517
Bonacquisto P, Modica GD, Petralia G, Tomarchio O (2014) A procurement auction market to trade residual cloud computing capacity. IEEE Trans Cloud Comput 3(3):345–357. doi:10.1109/TCC.2014.2369435
Rohitratana J, Altmann J (2012) Impact of pricing schemes on a market for Software-as-a-Service and perpetual software. Future Gener Computer Syst 28(8):1328–1339
Li H, Liu J, Tang G (2011) A pricing algorithm for cloud computing resources. In: 2011 international conference on network computing and information security (NCIS), 2011. IEEE, pp 69–73
Rohitratana J, Altmann J (2010) Agent-based simulations of the software market under different pricing schemes for Software-as-a-Service and perpetual software. In: Altmann et al. (eds) Economics of grids, clouds, systems, and services, ser Lecture Notes in Computer Science. Springer, Berlin/Heidelberg
Ruiz-Agundez I, Penya YK, Bringas PG (2011) A flexible accounting model for cloud computing. In: 2011 Annual SRII global conference (SRII), 2011. IEEE, pp 277–284
Triplett JE (2004) Handbook on hedonic indexes and quality adjustments in price indexes. science, technology and industry working papers. OECD publishing, Paris
Goodman AC (1978) Hedonic prices, price indices and housing markets. J Urban Econ 5(4):471–484
Griliches Z (1961) Hedonic price indexes for automobiles: an econometric of quality change. In: The price statistics of the Federal Goverment. NBER, pp 173–196
Chanel O, Gérard-Varet L-A, Ginsburgh V (1996) The relevance of hedonic price indices. J Cult Econ 20(1):1–24
Rosen S (1974) Hedonic prices and implicit markets: product differentiation in pure competition. J Political Econ 92:34–55
Pakes A (2002) A reconsideration of hedonic price indices with an application to PC’s. National Bureau of Economic Research. No. w8715, National Bureau of Economic Research
Berndt ER, Griliches Z, Rappaport NJ (1995) Econometric estimates of price indexes for personal computers in the 1990’s. J Econ 68(1):243–268
Moreau A (1996) Methodology of the price index for microcomputers and printers in France. Ind Prod Int Comp Meas Issues 99–118
Varoutas D, Deligiorgi K, Michalakelis C, Sphicopoulos T (2008) A hedonic approach to estimate price evolution of telecommunication services: evidence from Greece. Appl Econ Lett 15(14):1131–1134
Berndt ER (1991) The practice of econometrics: classic and contemporary. Addison-Wesley Publishing, Boston
Czarnul P (2013) An evaluation engine for dynamic ranking of cloud providers. Informatica 37(2):123
Okraszewski M (2015) Cloudorado launches new cloud computing comparison service. prweb.com. http://www.prweb.com/releases/cloud/computing/prweb12455967.htm. Accessed 29 Jan 2015
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Mitropoulou, P., Filiopoulou, E., Michalakelis, C. et al. Pricing cloud IaaS services based on a hedonic price index. Computing 98, 1075–1089 (2016). https://doi.org/10.1007/s00607-016-0493-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00607-016-0493-x