A Decision Support Model for Cloud Bursting
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A Decision Support Model for Cloud Bursting Cloud bursting combines the advantages of private and public clouds by adding external resources when internal resources are insufficient. Private clouds are still less expensive and remain under the control of the owner, but public cloud resources of any size are available on demand. The article suggests a decision support model to compute the optimal amount of internal resources and cost reductions. DOI 10.1007/s12599-013-0257-5
The Author Dr. Markus Lilienthal ()
E-FinanceLab RuW-Gebäude, Raum 1.218 Goethe-Universität Frankfurt Grüneburgplatz 1 60323 Frankfurt am Main Germany [email protected] Received: 2011-11-28 Accepted: 2012-11-06 Accepted after two revisions by Prof. Dr. Bichler. Published online: 2013-02-28 This article is also available in German in print and via http://www. wirtschaftsinformatik.de: Lilienthal M (2013) Ein Entscheidungsmodell für Cloud-Bursting. WIRTSCHAFTSINFORMATIK. doi: 10.1007/s11576-013 -0357-3. © Springer Fachmedien Wiesbaden 2013
1 Introduction Cloud computing (Weinhardt et al. 2009) has gained notable popularity in the past few years. With this paradigm, users may buy computing resources as a scalable utility service. Gartner Market Research estimates that this infrastructure, as a service market, will grow from $3.7 billion in 2011 to $10.5 billion in 2014 (Pettey 2011). Already in 2011, cloud computing has become a top technology priority (Luftman and Zadeh 2011; Moore 2011). Yet many enterprises still have doubts about public cloud computing (Pettey and Tudor 2010) and prefer to rely on private clouds, constrained to one enterBusiness & Information Systems Engineering
prise or to a cluster of trustworthy enterprises (i.e., community clouds). Cloud bursting (Kailasam et al. 2010) is sometimes used synonymously with the terms augmented cloud computing (Assunção et al. 2009; Reynolds and Bess 2009) or hybrid clouds (Armbrust et al. 2010; Mateescu et al. 2011). It offers a further, mixed strategy that can offload some workload onto public clouds (external providers) and thus obtain infrastructure as a service when internal resources are not sufficient. Mainstream adoption of cloud bursting is likely five to ten years away (Smith 2011); the adoption of cloud computing remains a complex decision. This article focuses on the economic aspect of cloud computing in order to develop an economic decision model that determines the optimal size of internal resources and the resulting cost savings achieved through cloud bursting. Consideration of workload distributions and especially demand volatility are central to this issue. The model relies on a modification of classical lease-or-buy models to address this requirement. The model recognizes that public cloud resources usually are more expensive than internal resources when fully utilized. Therefore, bursting is the economically optimal strategy, on condition that the right size of the private (internal) cloud resources is chosen. As a purely economic model, the model presumes that cloud
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