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A game-based resource pricing and allocation mechanism for profit maximization in cloud computing

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Abstract

In cloud computing environment, Software as a Service (SaaS) providers offer diverse software services to customers and commonly host their applications and data on the infrastructures supplied by Infrastructure as a Service (IaaS) providers. From the perspective of economics, the basic challenges for both SaaS and IaaS providers are to design resource pricing and allocation policies to maximize their own final revenue. However, IaaS providers seek an optimal price policy of virtual machines to generate more revenue, while SaaS providers want to minimize the cost of using infrastructure resources, and comply with service-level agreement contracts with users at the same time. In this situation, there exists conflict in maximizing revenue of both IaaS and SaaS providers simultaneously. In this paper, we model this revenue maximization problem as the Stackelberg game and analyze the existence and uniqueness of the game equilibrium. Moreover, considering the impact of resource price on users’ willing to access service, we propose a dynamic pricing mechanism to maximize the revenue of both SaaS and IaaS providers. The simulation results demonstrate that, compared to fixed pricing and auction-based pricing mechanisms, the proposed mechanism is superior in the revenue maximization and resource utilization.

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References

  • Abundo M, Di Valerio V, Cardellini V, Presti FL (2014) Bidding strategies in QoS-aware cloud systems based on N-armed bandit problems. In: Network cloud computing and applications (NCCA), 2014 IEEE 3rd symposium on. IEEE, pp 38–45

  • Agmon Ben-Yehuda O, Ben-Yehuda M, Schuster A, Tsafrir D (2013) Deconstructing Amazon EC2 spot instance pricing. ACM Trans Econ Comput 1(3):16

    Article  Google Scholar 

  • Amazon (2016) Amazon EC2 pricing. https://aws.amazon.com/ec2/pricing/. Accessed 26 Dec 2016

  • Anselmi J, Ardagna D, Passacantando M (2014) Generalized Nash equilibria for SAAS/PAAS clouds. Eur J Oper Res 236(1):326–339

    Article  MathSciNet  Google Scholar 

  • Ardagna D, Panicucci B, Passacantando M (2013) Generalized Nash equilibria for the service provisioning problem in cloud systems. IEEE Trans Serv Comput 6(4):429–442

    Article  Google Scholar 

  • Bonacquisto P, Di Modica G, Petralia G, Tomarchio O (2014) Procurement auctions to maximize players’ utility in cloud markets. In: CLOSER, pp 38–49

  • Bonacquisto P, Di Modica G, Petralia G, Tomarchio O (2015) A procurement auction market to trade residual cloud computing capacity. IEEE Trans Cloud Comput 3(3):345–357

    Article  Google Scholar 

  • Di Modica G, Petralia G, Tomarchio O (2013) Procurement auctions to trade computing capacity in the cloud. In: P2P, parallel, grid, cloud and internet computing (3PGCIC), 2013 eighth international conference on. IEEE, pp 298–305

  • Di Valerio V, Cardellini V, Presti FL (2013) Optimal pricing and service provisioning strategies in cloud systems: a Stackelberg game approach. In: 2013 IEEE sixth international conference on cloud computing. IEEE, pp 115–122

  • Feng G, Garg S, Buyya R, Li W (2012) Revenue maximization using adaptive resource provisioning in cloud computing environments. In: Proceedings of the 2012 ACM/IEEE 13th international conference on grid computing. IEEE Computer Society, pp 192–200

  • Goudarzi H, Pedram M (2011) Multi-dimensional SLA-based resource allocation for multi-tier cloud computing systems. In: Cloud computing (CLOUD), 2011 IEEE international conference on. IEEE, pp 324–331

  • Hassan MM, Hossain MS, Sarkar AJ, Huh EN (2014) Cooperative game-based distributed resource allocation in horizontal dynamic cloud federation platform. Inf Syst Front 16(4):523–542

    Article  Google Scholar 

  • Javadi B, Thulasiram RK, Buyya R (2013) Characterizing spot price dynamics in public cloud environments. Future Gener Comput Syst 29(4):988–999

    Article  Google Scholar 

  • Lampe U, Siebenhaar M, Papageorgiou A, Schuller D, Steinmetz R (2012) Maximizing cloud provider profit from equilibrium price auctions. In: Cloud computing (CLOUD), 2012 IEEE 5th international conference on. IEEE, pp 83–90

  • Macías M, Guitart J (2014) Sla negotiation and enforcement policies for revenue maximization and client classification in cloud providers. Future Gener Comput Syst 41:19–31

    Article  Google Scholar 

  • Mashayekhy L, Nejad MM, Grosu D (2015) Cloud federations in the sky: formation game and mechanism. IEEE Trans Cloud Comput 3(1):14–27

    Article  Google Scholar 

  • Microsoft (2016) Microsoft azure pricing. https://azure.microsoft.com/en-us/pricing/?b=16.45. Accessed 26 Dec 2016

  • Pillai PS, Rao S (2016) Resource allocation in cloud computing using the uncertainty principle of game theory. IEEE Syst J 10(2):637–648

    Article  Google Scholar 

  • Prasad AS, Rao S (2014) A mechanism design approach to resource procurement in cloud computing. IEEE Trans Comput 63(1):17–30

    Article  MathSciNet  Google Scholar 

  • Prasad VG, Rao S, Prasad AS (2012) A combinatorial auction mechanism for multiple resource procurement in cloud computing. In: 2012 12th international conference on intelligent systems design and applications (ISDA). IEEE, pp 337–344

  • Samimi P, Teimouri Y, Mukhtar M (2016) A combinatorial double auction resource allocation model in cloud computing. Inf Sci 357(C):201–216

    Article  Google Scholar 

  • Sim KM (2015) Agent-based interactions and economic encounters in an intelligent intercloud. IEEE Trans Cloud Comput 3(3):358–371

    Article  Google Scholar 

  • Song Y, Zafer M, Lee KW (2012) Optimal bidding in spot instance market. In: INFOCOM, 2012 proceedings IEEE. IEEE, pp 190–198

  • Sun Z, Zhu Z, Chen L, Xu H, Huang L (2014) A combinatorial double auction mechanism for cloud resource group-buying. In: 2014 IEEE 33rd international performance computing and communications conference (IPCCC). IEEE, pp 1–8

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

    Article  Google Scholar 

  • Truong-Huu T, Tham CK (2014) A novel model for competition and cooperation among cloud providers. IEEE Trans Cloud Comput 2(3):251–265

    Article  Google Scholar 

  • Wang X, Chen X, Wu W, An N, Wang L (2016) Cooperative application execution in mobile cloud computing: a Stackelberg game approach. IEEE Commun Lett 20(5):946–949

    Article  Google Scholar 

  • Wee S (2011) Debunking real-time pricing in cloud computing. In: Cluster, cloud and grid computing (CCGrid), 2011 11th IEEE/ACM international symposium on. IEEE, pp 585–590

  • Wu L, Garg SK, Versteeg S, Buyya R (2014) Sla-based resource provisioning for hosted software-as-a-service applications in cloud computing environments. IEEE Trans Serv Comput 7(3):465–485

    Article  Google Scholar 

  • Zaman S, Grosu D (2013a) Combinatorial auction-based allocation of virtual machine instances in clouds. J Parallel Distrib Comput 73(4):495–508

    Article  Google Scholar 

  • Zaman S, Grosu D (2013b) A combinatorial auction-based mechanism for dynamic VM provisioning and allocation in clouds. IEEE Trans Cloud Comput 1(2):129–141

    Article  Google Scholar 

  • Zhang Q, Zhu Q, Boutaba R (2011) Dynamic resource allocation for spot markets in cloud computing environments. In: Utility and cloud computing (UCC), 2011 fourth IEEE international conference on. IEEE, pp 178–185

  • Zheng Z, Gui Y, Wu F, Chen G (2015) Star: strategy-proof double auctions for multi-cloud, multi-tenant bandwidth reservation. IEEE Trans Comput 64(7):2071–2083

    Article  MathSciNet  Google Scholar 

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Acknowledgements

The authors would like to acknowledge that this work was partially supported by the National Natural Science Foundation of China (Grant Nos. 61379111, 61672537, 61672539, 61402538).

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Authors and Affiliations

  1. School of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha, 410114, China

    Zhengfa Zhu

  2. School of Information Science and Engineering, Central South University, Changsha, 410075, China

    Jun Peng, Kaiyang Liu & Xiaoyong Zhang

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  1. Zhengfa Zhu
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  2. Jun Peng
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  3. Kaiyang Liu
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  4. Xiaoyong Zhang
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Correspondence to Zhengfa Zhu or Xiaoyong Zhang.

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Zhu, Z., Peng, J., Liu, K. et al. A game-based resource pricing and allocation mechanism for profit maximization in cloud computing. Soft Comput 24, 4191–4203 (2020). https://doi.org/10.1007/s00500-019-04183-0

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