Skip to main content
Log in

A Survey on Spot Pricing in Cloud Computing

  • Published:
Journal of Network and Systems Management Aims and scope Submit manuscript

Abstract

Amazon offers spot instances to cloud customers using an auction-like mechanism. These instances are dynamically priced and offered at a lower price with less guarantee of availability. Observing the popularity of Amazon spot instances among the cloud users, research has intensified on defining the users’ and providers’ behavior in the spot market. This work presents an exhaustive survey of spot pricing in cloud ecosystem. An insight into the Amazon spot instances and its pricing mechanism has been presented for better understanding of the spot ecosystem. Spot pricing and resource provisioning problem, modeled as a market mechanism, is discussed from both computational and economics perspective. A significant amount of important research papers related to price prediction and modeling, spot resource provisioning, bidding strategy designing etc. are summarized and categorized to evaluate the state of the art in the context. All theoretical frameworks, developed for cloud spot market, are illustrated and compared in terms of the techniques and their findings. Finally, research gaps are identified and various economic and computational challenges in cloud spot ecosystem are discussed as a guide to the future research.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15

Similar content being viewed by others

References

  1. Zhang, Q., Cheng, L., Boutaba, R.: Cloud computing: state-of-the-art and research challenges. J. Internet Serv. Appl. 1, 7–18 (2010)

    Article  Google Scholar 

  2. Sajid, M., Raza, Z.: Cloud computing: issues and challenges. In: International Conference on Cloud, Big Data and Trust, pp. 35–41 (2013)

  3. Mell, P., Grance, T.: The NIST definition of cloud computing recommendations of the national institute of standards and technology. NIST Spec. Publ. 145, 7 (2011)

    Google Scholar 

  4. Xu, H., Li, B.: Dynamic cloud pricing for revenue maximization. IEEE Trans. Cloud Comput. 1, 158–171 (2013)

    Article  Google Scholar 

  5. Di Modica, G., Petralia, G., Tomarchio, O.: Procurement auctions to trade computing capacity in the cloud. In: Proceedings—2013 8th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing, 3PGCIC 2013, pp. 298–305 (2013)

  6. Zaman, S., Grosu, D.: Combinatorial auction-based allocation of virtual machine instances in clouds. J. Parallel Distrib. Comput. 73, 495–508 (2013)

    Article  Google Scholar 

  7. Narahari, Y., Raju, C.V.L., Ravikumar, K., Shah, S.: Dynamic pricing models for electronic business. Sadhana. 30, 231–256 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  8. Bichler, M., Kalagnanam, J., Katircioglu, K., King, A.J., Lawrence, R.D., Lee, H.S., Lin, G.Y., Lu, Y.: Applications of flexible pricing in business-to-business electronic commerce. IBM Syst. J. 41, 287–302 (2002)

    Article  Google Scholar 

  9. Suter, T.A., Hardesty, D.M.: Maximizing earnings and price fairness perceptions in online consumer-to-consumer auctions. J. Retail. 81, 307–317 (2005)

    Article  Google Scholar 

  10. AWS: Amazon EC2 Spot Instances, https://aws.amazon.com/ec2/spot/

  11. Barr, J.: EC2 Spot Pricing, Amazon (2011)

  12. Zhou, A.C., He, B., Liu, C.: Monetary cost optimizations for hosting workflow-as-a-service in IaaS clouds. IEEE Trans. Cloud Comput. 4, 34–48 (2016). https://doi.org/10.1109/TCC.2015.2404807

    Article  Google Scholar 

  13. Nash, P.G.: Introducing Preemptible VMs, a new class of compute available at 70% off standard pricing

  14. Chohan, N., Castillo, C., Spreitzer, M., Steinder, M.: See spot run: using spot instances for MapReduce workflows. HotCloud 2010(10), 1–7 (2012)

    Google Scholar 

  15. Mattess, M., Vecchiola, C., Buyya, R.: Managing peak loads by leasing cloud infrastructure services from a spot market. In: Proceedings—2010 12th IEEE International Conference on High Performance Computing and Communications, HPCC 2010, pp. 180–188 (2010)

  16. Wee, S.: Debunking real-time pricing in cloud computing. In: Proceedings—11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2011, pp. 585–590 (2011)

  17. Toosi, A.N., Vanmechelen, K., Khodadadi, F., Buyya, R.: An auction mechanism for cloud spot markets. ACM Trans. Auton. Adapt. Syst. 11, 2:1–2:33 (2016)

    Article  Google Scholar 

  18. Song, K., Yao, Y., Golubchik, L.: Improving the revenue, efficiency and reliability in data center spot market: A truthful mechanism. In: Proceedings—IEEE Computer Society’s Annual International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems, MASCOTS, pp. 222–231. IEEE (2013)

  19. Javadi, B., Thulasiramy, R.K., Buyya, R.: Statistical modeling of spot instance prices in public cloud environments. In: Proceedings—2011 4th IEEE International Conference on Utility and Cloud Computing, UCC 2011, pp. 219–228 (2011)

  20. Nadjaran Toosi, A., Khodadadi, F., Buyya, R.: SipaaS: Spot instance pricing as a Service framework and its implementation in OpenStack. Concurr. Comput. 28, 3672–3690 (2016). https://doi.org/10.1002/cpe.3749

    Article  Google Scholar 

  21. Toosi, A.N., Calheiros, R.N., Thulasiram, R.K., Buyya, R.: Resource provisioning policies to increase IaaS provider’s profit in a federated cloud environment. In: Proceedings—2011 IEEE International Conference on HPCC 2011—2011 IEEE International Workshop on FTDCS 2011—Workshops of the 2011 International Conference on UIC 2011—Workshops of the 2011 International Conference on ATC 2011, pp. 279–287. IEEE (2011)

  22. Liu, H.: Cutting MapReduce Cost with Spot Market. USENIX HotCloud’11, p. 5 (2011)

  23. Dubois, D.J., Casale, G.: OptiSpot: minimizing application deployment cost using spot cloud resources. Cluster Comput. 19, 893–909 (2016)

    Article  Google Scholar 

  24. Leslie, L.M., Lee, Y.C., Zomaya, A.Y.: RAMP: reliability-aware elastic instance provisioning for profit maximization. J. Supercomput. 71, 4529–4554 (2015)

    Article  Google Scholar 

  25. Marathe, A., Harris, R., Lowenthal, D., de Supinski, B., Rountree, B., Schulz, M.: Exploiting redundancy and application scalability for cost-effective, time-constrained execution of HPC applications on Amazon EC2. In: IEEE Transactions on Parallel and Distributed Systems, p. 1 (2015)

  26. Zhang, Q., Zhu, Q., Boutaba, R.: Dynamic resource allocation for spot markets in cloud computing environments. In: 2011 Fourth IEEE International Conference on Utility and Cloud Computing, pp. 178–185 (2011)

  27. Guo, W., Chen, K., Wu, Y., Zheng, W.: Bidding for highly available services with low price in spot instance market. In: Proceedings of the 24th International Symposium on High-Performance Parallel and Distributed Computing—HPDC’15, pp. 191–202. ACM Press, New York, New York, USA (2015)

  28. Chen, J., Wang, C., Zhou, B.B., Sun, L., Lee, Y.C., Zomaya, A.Y.: Tradeoffs between profit and customer satisfaction for service provisioning in the cloud. In: Proceedings of 20th International Symposium on High-Performance Parallel and Distributed Computing—HPDC’11. 229 (2011)

  29. Amazon: Amazon EC2 API Tools: Developer Tools: Amazon Web Services, http://aws.amazon.com/developertools/351

  30. Ben-Yehuda, O.A., Ben-Yehuda, M., Schuster, A., Tsafrir, D.: Deconstructing Amazon EC2 spot instance pricing. In: Proceedings—2011 3rd IEEE International Conference on Cloud Computing Technology and Science CloudCom 2011, vol. 1, pp. 304–311 (2011)

  31. Vermeersch, K.: Spotwatch, http://spotwatch.eu/input

  32. Zheng, L., Joe-Wong, C., Tan, C.W., Chiang, M., Wang, X.: How to bid the cloud. In: ACM Conference on Special Interest Group on Data Communication (SIGCOMM 2015), pp. 71–84 (2015)

  33. Kushwaha, V., Simmhan, Y.: Cloudy with a spot of opportunity: analysis of spot-priced VMs for practical job scheduling. In: 2014 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM), pp. 1–8. IEEE (2014)

  34. Javadi, B., Thulasiram, R.K., Buyya, R.: Characterizing spot price dynamics in public cloud environments. Futur. Gener. Comput. Syst. 29, 988–999 (2013)

    Article  Google Scholar 

  35. Wang, P., Qi, Y., Hui, D., Rao, L., Liu, X.: Present or future: optimal pricing for spot instances. In: Proceedings—International Conference on Distributed Computing Systems, pp. 410–419 (2013)

  36. Dawoud, W., Takouna, I., Meinel, C.: Reliable approach to sell the spare capacity in the cloud. Cloud Comput., pp. 229–236 (2012)

  37. Mihailescu, M., Teo, Y.M.: The impact of user rationality in federated clouds. In: 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012), pp. 620–627. IEEE (2012)

  38. Danak, A., Mannor, S.: Resource allocation with supply adjustment in distributed computing systems. In: Proceedings—International Conference on Distributed Computing Systems, pp. 498–506. IEEE (2010)

  39. Mihailescu, M., Teo, Y.M.: Strategy-proof dynamic resource pricing of multiple resource types on federated clouds. Presented at the (2010)

  40. Wang, Q., Ren, K., Meng, X.: When cloud meets eBay: towards effective pricing for cloud computing. In: Proceedings—IEEE INFOCOM, pp. 936–944 (2012)

  41. Lehmann, D., O’Callaghan, L.I.: Truth revelation in approximately efficient combinatorial auctions. J. ACM 49, 1–35 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  42. Wang, W., Liang, B., Li, B.: Revenue maximization with dynamic auctions in IaaS cloud markets. In: IEEE International Workshop on Quality of Service, IWQoS, pp. 57–62 (2013)

  43. Song, K., Yao, Y., Golubchik, L.: Exploring the profit-reliability trade-off in Amazon’s spot instance market: a better pricing mechanism. In: IEEE International Workshop on Quality of Service, IWQoS, pp. 119–128 (2013)

  44. Wang, W., Li, B., Liang, B.: Towards optimal capacity segmentation with hybrid cloud pricing. In: Proceedings—International Conference on Distributed Computing Systems, pp. 425–434 (2012)

  45. Abhishek, V., Kash, I.A., Key, P.: Fixed and market pricing for cloud services. In: Proceedings—IEEE INFOCOM, pp. 157–162 (2012)

  46. Sowmya, K., Sundarraj, R.P.: Generalized second price auction for relatively ranked heterogeneous spot instances in the cloud. In: 2013 5th International Conference on Advanced Computing, ICoAC 2013, pp. 304–310 (2014)

  47. Valerio, V. Di, Cardellini, V., Presti, F. Lo: Optimal pricing and service provisioning strategies in cloud systems: a stackelberg game approach. In: IEEE International Conference on Cloud Computing, CLOUD, pp. 115–122 (2013)

  48. Ma, D., Huang, J.: The pricing model of cloud computing services. In: Proceedings of the 14th Annual International Conference on Electronic Commerce—ICEC’12, pp. 263–269. ACM Press, New York, New York, USA (2012)

  49. Sowmya, K., Sundarraj, R.P.: On using prisoner dilemma model to explain cloud, pp. 206–215 (2013)

  50. Sowmya, K., Sundarraj, R.P.: Strategic bidding for cloud resources under dynamic pricing schemes. In: Proceedings—2012 International Symposium on Cloud and Services Computing, ISCOS 2012, pp. 25–30 (2013)

  51. Mazzucco, M., Dumas, M.: Achieving performance and availability guarantees with spot instances. In: Proceedings—2011 IEEE International Conference on HPCC 2011—2011 IEEE International Workshop on FTDCS 2011—Workshops of the 2011 International Conference on UIC 2011—Workshops of the 2011 International Conference on ATC 2011, pp. 296–303 (2011)

  52. Tang, S., Yuan, J., Wang, C., Li, X.Y.: A framework for Amazon EC2 bidding strategy under SLA constraints. IEEE Trans. Parallel Distrib. Syst. 25, 2–11 (2014)

    Article  Google Scholar 

  53. Toosi, A.N., Vanmechelen, K., Ramamohanarao, K., Buyya, R.: Revenue maximization with optimal capacity control in infrastructure as a service cloud markets. IEEE Trans. Cloud Comput. 3, 261–274 (2015)

    Article  Google Scholar 

  54. Zafer, M., Song, Y., Lee, K.W.: Optimal bids for spot VMs in a cloud for deadline constrained jobs. In: Proceedings—2012 IEEE 5th International Conference on Cloud Computing, CLOUD 2012, pp. 75–82 (2012)

  55. Song, Y., Zafer, M., Lee, K.W.: Optimal bidding in spot instance market. In: Proceedings—IEEE INFOCOM, pp. 190–198 (2012)

  56. Vintila, A., Oprescu, A.-M., Kielmann, T.: Fast (re-)configuration of mixed on-demand and spot instance pools for high-throughput computing. In: Proceedings of the First ACM Workshop on Optimization Techniques for Resources Management in Clouds, pp. 25–32. ACM, New York, NY, USA (2013)

  57. Jung, D., Suh, T., Yu, H., Gil, J.: A workflow scheduling technique using genetic algorithm in spot instance-based cloud. KSII Trans. Internet Inf. Syst. 8, 3126–3145 (2014)

    Google Scholar 

  58. Menache, I., Shamir, O., Jain, N.: On-demand, spot, or both: Dynamic resource allocation for executing batch jobs in the cloud. In: 11th International Conference on Autonomic Computing (ICAC 14), pp. 177–187 (2014)

  59. Wu, X., Loiseau, P., Hyytia, E.: Towards designing cost-optimal policies to utilize IaaS clouds with online learning. In: 2017 International Conference on Cloud and Autonomic Computing (ICCAC), pp. 160–171. IEEE (2017)

  60. Chu, H.-Y., Simmhan, Y.: Cost-efficient and resilient job life-cycle management on hybrid clouds. In: 2014 IEEE 28th International Parallel and Distributed Processing Symposium, pp. 327–336. IEEE (2014)

  61. Zhao, H., Pan, M., Liu, X., Li, X., Fang, Y.: Optimal resource rental planning for elastic applications in cloud market. In: Proceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium, IPDPS 2012, pp. 808–819. IEEE (2012)

  62. Arevalos, S., Lopez-Pires, F., Baran, B.: A comparative evaluation of algorithms for auction-based cloud pricing prediction. In: Proceedings—2016 IEEE International Conference on Cloud Engineering, IC2E 2016: Co-located with the 1st IEEE International Conference on Internet-of-Things Design and Implementation, IoTDI 2016, pp. 99–108 (2016)

  63. Wallace, R.M., Turchenko, V., Sheikhalishahi, M., Turchenko, I., Shults, V., Vazquez-Poletti, J.L., Grandinetti, L.: Applications of neural-based spot market prediction for cloud computing. In: Proceedings of the 2013 IEEE 7th International Conference on Intelligent Data Acquisition and Advanced Computing Systems, IDAACS 2013, pp. 710–716 (2013)

  64. Singh, V.K., Dutta, K.: Dynamic price prediction for amazon spot instances. In: Proceedings of the Annual Hawaii International Conference on System Sciences, pp. 1513–1520. IEEE (2015)

  65. Kamiński, B., Szufel, P.: On optimization of simulation execution on Amazon EC2 spot market. Simul. Model. Pract. Theory 58, 172–187 (2015)

    Article  Google Scholar 

  66. Lu, S., Li, X., Wang, L., Kasim, H., Palit, H., Hung, T., Legara, E.F.T., Lee, G.: A dynamic hybrid resource provisioning approach for running large-scale computational applications on cloud spot and on-demand instances. In: Proceedings of the International Conference on Parallel and Distributed Systems—ICPADS, pp. 657–662 (2013)

  67. Chaisiri, S., Kaewpuang, R., Lee, B.S., Niyato, D.: Cost minimization for provisioning virtual servers in amazon elastic compute cloud. In: IEEE International Workshop on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems—Proceedings, pp. 85–95 (2011)

  68. Dadashov, E., Cetintemel, U., Kraska, T.: Putting analytics on the spot: or how to lower the cost for analytics. IEEE Internet Comput. 18, 70–73 (2014)

    Article  Google Scholar 

  69. Chen, C., Lee, B.S., Tang, X.: Improving hadoop monetary efficiency in the cloud using spot instances. In: Proceedings of the International Conference on Cloud Computing Technology and Science, CloudCom, pp. 312–319 (2015)

  70. Taifi, M., Shi, J.Y.: Performance and reliability effects of multi-tier bidding on mapreduce in auction-based clouds. In: Proceedings—2013 IEEE 7th International Symposium on Service-Oriented System Engineering, SOSE 2013, pp. 61–71. IEEE (2013)

  71. Dadashov, E., Kraska, T.: Spotlytics: How to use cloud market places for analytics? Fachtagung Datenbanksysteme für Business, Technol. und Web, pp. 361–380 (2017)

  72. Koo, R., Toueg, S.: Checkpointing and rollback-recovery for distributed systems. IEEE Trans. Softw. Eng. SE-13, 23–31 (1987)

    Article  MATH  Google Scholar 

  73. Yi, S., Andrzejak, A., Kondo, D.: Monetary cost-aware checkpointing and migration on amazon cloud spot instances. IEEE Trans. Serv. Comput. 5, 512–524 (2012)

    Article  Google Scholar 

  74. Yi, S., Kondo, D., Andrzejak, A.: Reducing costs of spot instances via checkpointing in the Amazon Elastic Compute Cloud. In: Proceedings—2010 IEEE 3rd International Conference on Cloud Computing, CLOUD 2010, pp. 236–243 (2010)

  75. Khatua, S., Mukherjee, N.: Application-centric resource provisioning for Amazon EC2 spot instances. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 267–278. Springer (2013)

  76. Khatua, S., Mukherjee, N.: A novel checkpointing scheme for Amazon EC2 spot instances. In: Proceedings—13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2013, pp. 180–181 (2013)

  77. Khatua, S., Ghosh, A., Mukherjee, N.: Application-centric cloud management. In: Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA, pp. 9–15 (2011)

  78. Leslie, L.M., Lee, Y.C., Lu, P., Zomaya, A.Y.: Exploiting performance and cost diversity in the clouds. In: IEEE International Conference on Cloud Computing, CLOUD, pp. 107–114 (2013)

  79. Jung, D., Lim, J., Yu, H., Suh, T.: Estimated interval-based checkpointing (EIC) on spot instances in cloud computing. J. Appl. Math. (2014). https://doi.org/10.1155/2014/217547

    Google Scholar 

  80. Jung, D., Chin, S., Chung, K., Yu, H., Gil, J.: An efficient checkpointing scheme using price history of spot instances in cloud computing environment. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 185–200 (2011)

  81. Yi, S., Heo, J., Cho, Y., Hong, J.: Taking point decision mechanism for page-level incremental checkpointing based on cost analysis of process execution time. In: Journal of Information Science and Engineering, pp. 1325–1337 (2007)

  82. Poola, D., Ramamohanarao, K., Buyya, R.: Fault-tolerant workflow scheduling using spot instances on clouds. In: Procedia Computer Science, pp. 523–533 (2014)

  83. Jangjaimon, I., Tzeng, N.-F.: Effective cost reduction for elastic clouds under spot instance pricing through adaptive checkpointing. IEEE Trans. Comput. 64, 1 (2014)

    MathSciNet  MATH  Google Scholar 

  84. Voorsluys, W., Buyya, R.: Reliable provisioning of spot instances for compute-intensive applications. In: Proceedings—International Conference on Advanced Information Networking and Applications, AINA, pp. 542–549 (2012)

  85. He, X., Shenoy, P., Sitaraman, R., Irwin, D.: Cutting the cost of hosting online services using cloud spot markets. In: Proceedings of the 24th International Symposium on High-Performance Parallel and Distributed Computing—HPDC’15, pp. 207–218. ACM Press, New York, New York, USA (2015)

  86. Lim, S.H., Thakur, G.S., Horey, J.L.: Analyzing reliability of virtual machine instances with dynamic pricing in the public cloud. In: Proceedings of the International Parallel and Distributed Processing Symposium, IPDPS, pp. 885–893 (2014)

  87. Binnig, C., Salama, A., Zamanian, E., El-Hindi, M., Feil, S., Ziegler, T.: Spotgres—parallel data analytics on Spot Instances. In: Proceedings—International Conference on Data Engineering, pp. 14–21. IEEE (2015)

  88. Sharma, P., Lee, S., Guo, T., Irwin, D., Shenoy, P.: SpotCheck: designing a derivative IaaS cloud on the spot market. In: Proceedings of the Tenth European Conference on Computer Systems. p. 16:1–16:15. ACM, New York, NY, USA (2015)

  89. Voorsluys, W., Garg, S.K., Buyya, R.: Provisioning spot market cloud resources to create cost-effective virtual clusters. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 395–408 (2011)

  90. Calheiros, R.N., Vecchiola, C., Karunamoorthy, D., Buyya, R.: The Aneka platform and QoS-driven resource provisioning for elastic applications on hybrid Clouds. In: Future Generation Computer Systems, pp. 861–870 (2012)

  91. Cheng, T., Ying, W., Feng, Q., Bo, Y.: Decision model for provisioning virtual resources in Amazon EC2. 2012 8th International Conference on Network and Service Management (CNSM 2012), 22–26 Oct. 2012. 159–163 (2012)

  92. Knauth, T., Fetzer, C.: Spot-on for timed instances: Striking a balance between spot and on-demand instances. In: Proceedings—2nd International Conference on Cloud and Green Computing and 2nd International Conference on Social Computing and Its Applications, CGC/SCA 2012, pp. 105–112 (2012)

  93. Huang, H., Wang, L., Tak, B.C., Wang, L., Tang, C.: CAP3: a cloud auto-provisioning framework for parallel processing using on-demand and spot instances. In: IEEE International Conference on Cloud Computing, CLOUD, pp. 228–235 (2013)

  94. Vieira, C.C.A., Bittencourt, L.F., Madeira, E.R.M.: Reducing costs in cloud application execution using redundancy-based scheduling. In: Proceedings—2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing, UCC 2014, pp. 117–126 (2014)

  95. Pucher, A., Wolski, R., Krintz, C.: Using spot instance SLAs for reliable cloud federation (2015)

  96. Xu, Z., Stewart, C., Deng, N., Wang, X.: Blending on-demand and spot instances to lower costs for in-memory storage. In: IEEE International Conference on Computer Communications (2016)

  97. Dahiphale, D., Karve, R., Vasilakos, A.V., Liu, H., Yu, Z., Chhajer, A., Wang, J., Wang, C.: An Advanced MapReduce: cloud MapReduce, enhancements and applications. IEEE Trans. Netw. Serv. Manag. 11, 101–115 (2014)

    Article  Google Scholar 

  98. Monge, D.A., Garino, C.G.: Adaptive spot-instances aware autoscaling for scientific workflows on the cloud. Commun. Comput. Inf. Sci. 485, 13–27 (2014)

    Google Scholar 

  99. Qu, C., Calheiros, R.N.N., Buyya, R.: A reliable and cost-efficient auto-scaling system for web applications using heterogeneous spot instances. J. Netw. Comput. Appl. 65, 167–180 (2016)

    Article  Google Scholar 

  100. Wieder, A., Bhatotia, P., Post, A., Rodrigues, R.: Orchestrating the deployment of computations in the cloud with conductor. Usenix Nsdi 2012, p. 27 (2012)

  101. Taifi, M.: Banking on decoupling: Budget-driven sustainability for hpc applications on EC2 spot instances. In: Proceedings of the IEEE Symposium on Reliable Distributed Systems, pp. 442–447 (2012)

  102. Gong, Y., He, B., Zhou, A.C.: Monetary cost optimizations for MPI-based HPC applications on Amazon clouds. In: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis on—SC’15, pp. 1–12. ACM Press, New York, New York, USA (2015)

  103. Subramanya, S., Guo, T., Sharma, P., Irwin, D., Shenoy, P.: SpotOn. In: Proceedings of Sixth ACM Symposium on Cloud Computing—SoCC’15. 329–341 (2015)

  104. Kaulakienė, D., Thomsen, C., Pedersen, T.B., Çetintemel, U., Kraska, T.: SpotADAPT. In: Proceedings of the ACM Eighteenth International Workshop on Data Warehousing and OLAP—DOLAP’15, pp. 59–68. ACM Press, New York, New York, USA (2015)

  105. Andrzejak, A., Kondo, D., Sangho Yi: Decision model for cloud computing under SLA constraints. In: 2010 IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, pp. 257–266 (2010)

  106. Karunakaran, S., Sundarraj, R.: Bidding strategies for spot instances in cloud computing markets. IEEE Internet Comput. 19, 1 (2014)

    Google Scholar 

  107. Abundo, M., Di Valerio La Sapienza, V., Cardellini, V., Presti, F. Lo: QoS-aware bidding strategies for VM spot instances: a reinforcement learning approach applied to periodic long running jobs. In: Proceedings of the 2015 IFIP/IEEE International Symposium on Integrated Network Management, IM 2015, pp. 53–61. IEEE (2015)

  108. Abundo, M., Valerio, V. Di, Cardellini, V., Presti, F. Lo: Bidding strategies in QoS-aware cloud systems based on N-Armed bandit problems. In: Proceedings—IEEE 3rd Symposium on Network Cloud Computing and Applications, NCCA 2014, pp. 38–45 (2014)

  109. Dubois, D.J., Casale, G.: Autonomic provisioning and application mapping on spot cloud resources. In: 2015 International Conference on Cloud and Autonomic Computing, pp. 57–68. IEEE (2015)

  110. Li, Z., Kihl, M., Robertsson, A.: On a feedback control-based mechanism of bidding for cloud spot service. In: 2015 IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom), pp. 290–297. IEEE (2015)

  111. Wolski, R., Brevik, J.: Providing statistical reliability guarantees in the AWS spot tier. In: 24th High Performance Computing Symposium, p. 13 (2016)

  112. Ardagna, D., Ciavotta, M., Passacantando, M.: Generalized nash equilibria for the service provisioning problem in multi-cloud systems. IEEE Trans. Serv. Comput. 10, 381–395 (2015). https://doi.org/10.1109/TSC.2015.2477836

    Article  Google Scholar 

  113. Ribas, M., Furtado, C.G., de Souza, J.N., Barroso, G.C., Moura, A., Lima, A.S., Sousa, F.R.C.: A Petri net-based decision-making framework for assessing cloud services adoption: the use of spot instances for cost reduction. J. Netw. Comput. Appl. 57, 102–118 (2015)

    Article  Google Scholar 

  114. Daskalakis, C., Goldberg, P.W., Papadimitriou, C.H.: The complexity of computing a nash equilibrium. SIAM J. Comput. 39, 195–259 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  115. AWS, A.: Spot bid advisor, https://aws.amazon.com/ec2/spot/bid-advisor/

  116. Gomes, R.D., Sweeney, K.S., Acm: Bayes–Nash equilibria of the generalized second price auction. In: 10th ACM Conference on Electronic Commerce—Ec 2009, p. 107 (2009)

Download references

Acknowledgements

Authors would like to accord their sincere thanks to the anonymous reviewers of this manuscript for their suggestions resulting in quality improvement. Authors also would like to acknowledge UGC UPE-2 for their financial assistance of this manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Gaurav Baranwal.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kumar, D., Baranwal, G., Raza, Z. et al. A Survey on Spot Pricing in Cloud Computing. J Netw Syst Manage 26, 809–856 (2018). https://doi.org/10.1007/s10922-017-9444-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10922-017-9444-x

Keywords

Navigation