Abstract
The rapid standardization and specialization of cloud computing services have led to the development of cloud spot markets on which cloud service providers and customers can trade in near real-time. Frequent changes in demand and supply give rise to spot prices that vary throughout the day. Cloud customers often have temporal flexibility to execute their jobs before a specific deadline. In this paper, the authors apply real options analysis (ROA), which is an established valuation method designed to capture the flexibility of action under uncertainty. They adapt and compare multiple discrete-time approaches that enable cloud customers to quantify and exploit the monetary value of their short-term temporal flexibility. The paper contributes to the field by guaranteeing cloud job execution of variable-time requests in a single cloud spot market, whereas existing multi-market strategies may not fulfill requests when outbid. In a broad simulation of scenarios for the use of Amazon EC2 spot instances, the developed approaches exploit the existing savings potential up to 40 percent – a considerable extent. Moreover, the results demonstrate that ROA, which explicitly considers time-of-day-specific spot price patterns, outperforms traditional option pricing models and expectation optimization.
Similar content being viewed by others
References
Allenotor D, Thulasiram RK (2014) A discrete time financial option pricing model for cloud services. In: IEEE 11th international conference on ubiquitous intelligence and computing, Piscataway, pp 629–636
Alzaghoul E, Bahsoon R (2013) CloudMTD: using real options to manage technical debt in cloud-based service selection. In: 4th international workshop on managing technical debt, pp 55–62
Alzaghoul E, Bahsoon R (2014) Evaluating technical debt in cloud-based architectures using real options. In: 23rd Australian software engineering conference (ASWEC), pp 1–10
Amazon Web Services (2017) Amazon EC2 spot instances pricing. https://aws.amazon.com/ec2/spot/pricing/. Accessed 01 May 2017
Amenc N, Le Sourd V (2003) Portfolio theory and performance analysis. Wiley, Chichester
Amin KI (1991) On the computation of continuous time option prices using discrete approximations. J Financ Quant Anal 26(4):477–495. https://doi.org/10.2307/2331407
Amram M, Kulatilaka N (1999) Real options: managing strategic investment in an uncertain world. Harvard Business School Press, Boston
Andrzejak A, Kondo D, Yi S (2010) Decision model for cloud computing under SLA constraints. In: IEEE international symposium on modeling, analysis and simulation of computer and telecommunication systems, pp 257–266
Arevalos S, Lopez-Pires F, Baran B (2016) A comparative evaluation of algorithms for auction-based cloud pricing prediction. In: IEEE international conference on cloud engineering (IC2E), pp 99–108
Baughman M, Haas C, Wolski R, Foster I, Chard K (2018) Predicting Amazon spot prices with LSTM networks. In: Proceedings of the 9th workshop on scientific cloud computing (ScienceCloud’18). ACM Press, New York, pp 1–7
Benaroch M, Kauffman RJ (1999) A case for using real options pricing analysis to evaluate information technology project investments. Inf Syst Res 10(1):70–86. https://doi.org/10.1287/isre.10.1.70
Benaroch M, Kauffman RJ (2000) Justifying electronic banking network expansion using real options analysis. MIS Q 24(2):197–225. https://doi.org/10.2307/3250936
Ben-Yehuda OA, Ben-Yehuda M, Schuster A, Tsafrir D (2013) Deconstructing Amazon EC2 spot instance pricing. ACM Trans Econ Comput 1(3):1–20. https://doi.org/10.1145/2509413.2509416
Bestavros A, Krieger O (2014) Toward an open cloud marketplace: vision and first steps. IEEE Internet Comput 18(1):72–77. https://doi.org/10.1109/mic.2014.17
Black F, Scholes M (1973) The pricing of options and corporate liabilities. J Politic Econ 81(3):637–654. https://doi.org/10.1086/260062
Cai Z, Li X, Ruiz R, Li Q (2018) Price forecasting for spot instances in cloud computing. Future Gener Comput Syst 79(1):38–53. https://doi.org/10.1016/j.future.2017.09.038
Chen T, Zhang J, Lai K-K (2009) An integrated real options evaluating model for information technology projects under multiple risks. Int J Project Manag 27(8):776–786. https://doi.org/10.1016/j.ijproman.2009.01.001
Cheng HK, Li Z, Naranjo A (2016) Research note – cloud computing spot pricing dynamics: latency and limits to arbitrage. Inf Syst Res 27(1):145–165. https://doi.org/10.1287/isre.2015.0608
Cox JC, Ross SA, Rubinstein M (1979) Option pricing: a simplified approach. J Financ Econ 7(3):229–263. https://doi.org/10.1016/0304-405x(79)90015-1
Dadashov E, Cetintemel U, Kraska T (2014) Putting analytics on the spot: or how to lower the cost for analytics. IEEE Internet Comput 18(5):70–73. https://doi.org/10.1109/mic.2014.94
Ekwe-Ekwe N, Barker A (2018) Location, location, location: exploring Amazon EC2 spot instance pricing across geographical regions. In: 18th IEEE/ACM international symposium on cluster, cloud and grid computing (CCGRID), pp 370–373
Fridgen G, Häfner L, König C, Sachs T (2016) Providing utility to utilities: the value of information systems enabled flexibility in electricity consumption. J Assoc Inf Syst 17(8):537–563
Fridgen G, Keller R, Thimmel M, Wederhake L (2017) Shifting load through space – the economics of spatial demand side management using distributed data centers. Energ Polic 109:400–413. https://doi.org/10.1016/j.enpol.2017.07.018
Gregor S, Hevner AR (2013) Positioning and presenting design science research for maximum impact. MIS Q 37(2):337–355. https://doi.org/10.25300/misq/2013/37.2.01
Hull JC (2014) Options, futures, and other derivatives. Pearson, Upper Saddle River
Jarrow RA, Rudd A (1983) Option pricing. Irwin, Homewood
Javadi B, Thulasiramy RK, Buyya R (2011) Statistical modeling of spot instance prices in public cloud environments. In: IEEE 4th international conference on utility and cloud computing (UCC), Victoria, pp 219–228
Jede A, Teuteberg F (2016) Valuing the advantage of early termination: adopting real options theory for SaaS. In: 49th Hawaii international conference on system sciences, Koloa, pp 4880–4889
Kamiński B, Szufel P (2015) On optimization of simulation execution on Amazon EC2 spot market. Simul Model Pract Theor 58(2):172–187. https://doi.org/10.1016/j.simpat.2015.05.008
Karunakaran S, Sundarraj RP (2015) Bidding strategies for spot instances in cloud computing markets. IEEE Internet Comput 19(3):32–40. https://doi.org/10.1109/mic.2014.87
Keller R, König C (2014) A reference model to support risk identification in cloud networks. In: Proceedings of the 35th international conference on information systems (ICIS 2014), Auckland
Khandelwal V, Chaturvedi A, Gupta CP (2017) Amazon EC2 spot price prediction using regression random forests. IEEE transactions on cloud computing (Early Access). https://doi.org/10.1109/tcc.2017.2780159
Klaus C, Krause F, Ullrich C (2014) Determining the business value of volume flexibility for service providers – a real options approach. In: Proceedings of the 22nd European conference on information systems (ECIS), Tel Aviv
Kleinert A, Stich V (2010) Valuation of procurement flexibility in the machinery and equipment industry using the real option approach. In: Bernus P, Doumeingts G, Fox M (eds) Enterprise architecture, integration and interoperability. Springer, Heidelberg, pp 21–31
Kumar D, Baranwal G, Raza Z, Vidyarthi DP (2018) A survey on spot pricing in cloud computing. J Netw Syst Manag 26(4):809–856. https://doi.org/10.1007/s10922-017-9444-x
Laptev N, Yosinski J, Li LE, Smyl S (2017) Time-series extreme event forecasting with neural networks at Uber. In: Time series workshop at ICML 2017, Sydney
Lee Y-C, Lee S-S (2011) The valuation of RFID investment using fuzzy real option. Expert Syst Appl 38(10):12195–12201. https://doi.org/10.1016/j.eswa.2011.03.076
Leisen DPJ, Reimer M (1996) Binomial models for option valuation - examining and improving convergence. Appl Math Financ 3(4):319–346. https://doi.org/10.1080/13504869600000015
Lewis GA (2013) Role of standards in cloud-computing interoperability. In: 46th Hawaii international conference on system sciences, Wailea, pp 1652–1661
Li Z, Tärneberg W, Kihl M, Robertsson A (2016a) Using a predator-prey model to explain variations of cloud spot price. In: 6th international conference on cloud computing and services science, pp 51–58
Li Z, Zhang H, O’Brien L, Jiang S, Zhou Y, Kihl M, Ranjan R (2016b) Spot pricing in the cloud ecosystem: a comparative investigation. J Syst Softw 114:1–19. https://doi.org/10.1016/j.jss.2015.10.042
Lilienthal M (2013) A decision support model for cloud bursting. Bus Inf Syst Eng 5(2):71–81. https://doi.org/10.1007/s12599-013-0257-5
Loutas N, Kamateri E, Bosi F, Tarabanis K (2011a) Cloud computing interoperability: the state of play. In: IEEE 3rd international conference on cloud computing technology and science, Athens, pp 752–757
Loutas N, Kamateri E, Tarabanis K (2011b) A semantic interoperability framework for cloud platform as a service. In: IEEE 3rd international conference on cloud computing technology and science, Athens, pp 280–287
Marathe A, Harris R, Lowenthal D, Supinski BR de, Rountree B, Schulz M (2014) Exploiting redundancy for cost-effective, time-constrained execution of HPC applications on amazon EC2. In: 23rd international symposium on high-performance parallel and distributed computing (HPDC ‘14). ACM Press, New York, pp 279–290
Mazzucco M, Dumas M (2011) Achieving performance and availability guarantees with spot instances. In: IEEE 13th international conference on high performance computing and communications (HPCC), Banff, pp 296–303
Meinl T, Neumann D (2009) A real options model for risk hedging in grid computing scenarios. In: 42nd Hawaii international conference on system sciences, Waikoloa, pp 1–10
Mell PM, Grance T (2011) The NIST definition of cloud computing. National Institute of Standards and Technology, Gaithersburg
Myers SC (1977) Determinants of corporate borrowing. J Financ Econ 5(2):147–175. https://doi.org/10.1016/0304-405x(77)90015-0
Naldi M, Mastroeni L (2016) Economic decision criteria for the migration to cloud storage. Eur J Inf Syst 25(1):16–28. https://doi.org/10.1057/ejis.2014.34
Náplava P (2016) Evaluation of cloud computing hidden benefits by using real options analysis. Acta Inf Prag 5(2):162–179. https://doi.org/10.18267/j.aip.92
Nwankpa J, Roumani Y, Roumani YF (2016) Exploring ERP-enabled technology adoption: a real options perspective. Commun Assoc Inf Syst 39(24):529–555. https://doi.org/10.17705/1cais.03924
Rossi E, Spazzini F (2014) GARCH models for commodity markets. In: Roncoroni A, Fusai G, Cummins M (eds) Handbook of multi-commodity markets and products. Wiley, Chichester, pp 687–753
Skyhigh Networks (2017) Custom applications and IaaS trends 2017. https://downloads.cloudsecurityalliance.org/assets/survey/custom-applications-and-iaas-trends-2017.pdf. Accessed 01 Aug 2018
Tamrakar K, Yazidi A, Haugerud H (2017) Cost efficient batch processing in Amazon cloud with deadline awareness. In: IEEE 31st intlernational conference on advanced information networking and applications (AINA), pp 963–971
Tang S, Yuan J, Li X-Y (2012) Towards optimal bidding strategy for Amazon EC2 cloud spot instance. In: IEEE 5th international conference on cloud computing (CLOUD), Honolulu, pp 91–98
Tang S, Yuan J, Wang C, Li X-Y (2014) A framework for Amazon EC2 bidding strategy under SLA constraints. IEEE Trans Parallel Distrib Syst 25(1):2–11. https://doi.org/10.1109/tpds.2013.15
Tian Y (1993) A modified lattice approach to option pricing. J Future Market 13(5):563–577. https://doi.org/10.1002/fut.3990130509
Trigeorgis L (1996) Real options. J Financ 51(5):1974–1977. https://doi.org/10.2307/2329548
Ullrich C (2013) Valuation of IT investments using real options theory. Bus Inf Syst Eng 5(5):331–341. https://doi.org/10.1007/s12599-013-0286-0
United States Securities and Exchange Commission (US SEC) (2017) Snap Inc.: form S-1 registration statement. https://www.sec.gov/Archives/edgar/data/1564408/000119312517029199/d270216ds1.htm. Accessed 01 Aug 2018
van Hulle C (1988) Option pricing methods: an overview. Insur Math Econ 7(3):139–152. https://doi.org/10.1016/0167-6687(88)90071-6
Vieira CCA, Bittencourt LF, Madeira ERM (2015) A scheduling strategy based on redundancy of service requests on IaaS providers. In: 23rd Euromicro international conference on parallel, distributed, and network-based processing, Turku, pp 497–504
Wallace RM, Turchenko V, Sheikhalishahi M, Turchenko I, Shults V, Vazquez-Poletti JL, Grandinetti L (2013) Applications of neural-based spot market prediction for cloud computing. In: IEEE 7th international conference on intelligent data acquisition and advanced computing systems (IDAACS), pp 710–716
Wang GHK, Yau J (2000) Trading volume, bid-ask spread, and price volatility in futures markets. J Future Market 20(10):943–970. https://doi.org/10.1002/1096-9934(200011)20:10%3c943:aid-fut4%3e3.0.co;2-8
Wu F, Li HZ, Chu LK, Sculli D, Gao K (2009) An approach to the valuation and decision of ERP investment projects based on real options. Ann Oper Res 168(1):181–203. https://doi.org/10.1007/s10479-008-0365-7
Yam C-Y, Baldwin A, Shiu S, Ioannidis C (2011) Migration to cloud as real option: investment decision under uncertainty. In: IEEE 10th intlernational conference on trust, security and privacy in computing and communications (TrustCom), Changsha, pp 940–949
Zafer M, Song Y, Lee K-W (2012) Optimal bids for spot VMs in a cloud for deadline constrained jobs. In: IEEE 5th intlernational conference on cloud computing (CLOUD), Honolulu, pp 75–82
Zhang Y, Li B, Huang Z, Wang J, Zhu J, Peng H (2014) Strategy-proof auction mechanism with group price for virtual machine allocation in clouds. In: 2nd international conference on advanced cloud and big data (CBD), Huangshan, pp 60–68
Zheng L, Joe-Wong C, Tan CW, Chiang M, Wang X (2015) How to bid the cloud. ACM SIGCOMM Comput Commun Rev 45(5):71–84. https://doi.org/10.1145/2829988.2787473
Zimmermann S, Müller M, Heinrich B (2016) Exposing and selling the use of web services – an option to be considered in make-or-buy decision-making. Decis Support Syst 89:28–40. https://doi.org/10.1016/j.dss.2016.06.006
Author information
Authors and Affiliations
Corresponding author
Additional information
Accepted after two revisions by Natalia Kliewer.
Rights and permissions
About this article
Cite this article
Keller, R., Häfner, L., Sachs, T. et al. Scheduling Flexible Demand in Cloud Computing Spot Markets. Bus Inf Syst Eng 62, 25–39 (2020). https://doi.org/10.1007/s12599-019-00592-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12599-019-00592-5