IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v244y2015i2p637-647.html
   My bibliography  Save this article

Revenue management for Cloud computing providers: Decision models for service admission control under non-probabilistic uncertainty

Author

Listed:
  • Püschel, Tim
  • Schryen, Guido
  • Hristova, Diana
  • Neumann, Dirk

Abstract

Cloud computing promises the flexible delivery of computing services in a pay-as-you-go manner. It allows customers to easily scale their infrastructure and save on the overall cost of operation. However Cloud service offerings can only thrive if customers are satisfied with service performance. Allowing instantaneous access and flexible scaling while maintaining the service levels and offering competitive prices poses a significant challenge to Cloud computing providers. Furthermore services will remain available in the long run only if this business generates a stable revenue stream. To address these challenges we introduce novel policy-based service admission control models that aim at maximizing the revenue of Cloud providers while taking informational uncertainty regarding resource requirements into account. Our evaluation shows that policy-based approaches statistically significantly outperform first come first serve approaches, which are still state of the art. Furthermore the results give insights in how and to what extent uncertainty has a negative impact on revenue.

Suggested Citation

  • Püschel, Tim & Schryen, Guido & Hristova, Diana & Neumann, Dirk, 2015. "Revenue management for Cloud computing providers: Decision models for service admission control under non-probabilistic uncertainty," European Journal of Operational Research, Elsevier, vol. 244(2), pages 637-647.
    • Handle: RePEc:eee:ejores:v:244:y:2015:i:2:p:637-647
    DOI: 10.1016/j.ejor.2015.01.027
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221715000478
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2015.01.027?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hervé Moulin, 2007. "On Scheduling Fees to Prevent Merging, Splitting, and Transferring of Jobs," Mathematics of Operations Research, INFORMS, vol. 32(2), pages 266-283, May.
    2. Gabriel Bitran & René Caldentey, 2003. "An Overview of Pricing Models for Revenue Management," Manufacturing & Service Operations Management, INFORMS, vol. 5(3), pages 203-229, August.
    3. Zimmermann, H. -J., 2000. "An application-oriented view of modeling uncertainty," European Journal of Operational Research, Elsevier, vol. 122(2), pages 190-198, April.
    4. Constantinos Maglaras & Joern Meissner, 2006. "Dynamic Pricing Strategies for Multiproduct Revenue Management Problems," Manufacturing & Service Operations Management, INFORMS, vol. 8(2), pages 136-148, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Romanuke Vadim, 2015. "Optimal Training Parameters and Hidden Layer Neuron Number of Two-Layer Perceptron for Generalised Scaled Object Classification Problem," Information Technology and Management Science, Sciendo, vol. 18(1), pages 42-48, December.
    2. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2018. "Co-residence based data vulnerability vs. security in cloud computing system with random server assignment," European Journal of Operational Research, Elsevier, vol. 267(2), pages 676-686.
    3. Doan, Xuan Vinh & Lei, Xiao & Shen, Siqian, 2020. "Pricing of reusable resources under ambiguous distributions of demand and service time with emerging applications," European Journal of Operational Research, Elsevier, vol. 282(1), pages 235-251.
    4. Xiang Zhao & Xinghua Shan & Jinfei Wu, 2023. "The Impact of Seat Resource Fragmentation on Railway Network Revenue Management," Networks and Spatial Economics, Springer, vol. 23(1), pages 135-177, March.
    5. Chen, Li-Ming & Chang, Wei-Lun, 2020. "Under what conditions can an application service firm with in-house computing benefit from cloudbursting?," European Journal of Operational Research, Elsevier, vol. 282(1), pages 71-80.
    6. Klein, Robert & Koch, Sebastian & Steinhardt, Claudius & Strauss, Arne K., 2020. "A review of revenue management: Recent generalizations and advances in industry applications," European Journal of Operational Research, Elsevier, vol. 284(2), pages 397-412.
    7. Pascual, Fanny & Rzadca, Krzysztof, 2018. "Colocating tasks in data centers using a side-effects performance model," European Journal of Operational Research, Elsevier, vol. 268(2), pages 450-462.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yiwei Chen & Vivek F. Farias, 2013. "Simple Policies for Dynamic Pricing with Imperfect Forecasts," Operations Research, INFORMS, vol. 61(3), pages 612-624, June.
    2. Qi (George) Chen & Stefanus Jasin & Izak Duenyas, 2016. "Real-Time Dynamic Pricing with Minimal and Flexible Price Adjustment," Management Science, INFORMS, vol. 62(8), pages 2437-2455, August.
    3. Lingxiu Dong & Panos Kouvelis & Zhongjun Tian, 2009. "Dynamic Pricing and Inventory Control of Substitute Products," Manufacturing & Service Operations Management, INFORMS, vol. 11(2), pages 317-339, December.
    4. Pavithra Harsha & Shivaram Subramanian & Joline Uichanco, 2019. "Dynamic Pricing of Omnichannel Inventories," Service Science, INFORMS, vol. 21(1), pages 47-65, January.
    5. Stefanus Jasin, 2014. "Reoptimization and Self-Adjusting Price Control for Network Revenue Management," Operations Research, INFORMS, vol. 62(5), pages 1168-1178, October.
    6. Dasu, Sriram & Tong, Chunyang, 2010. "Dynamic pricing when consumers are strategic: Analysis of posted and contingent pricing schemes," European Journal of Operational Research, Elsevier, vol. 204(3), pages 662-671, August.
    7. Peter Seele & Claus Dierksmeier & Reto Hofstetter & Mario D. Schultz, 2021. "Mapping the Ethicality of Algorithmic Pricing: A Review of Dynamic and Personalized Pricing," Journal of Business Ethics, Springer, vol. 170(4), pages 697-719, May.
    8. Qi (George) Chen & Stefanus Jasin & Izak Duenyas, 2019. "Nonparametric Self-Adjusting Control for Joint Learning and Optimization of Multiproduct Pricing with Finite Resource Capacity," Mathematics of Operations Research, INFORMS, vol. 44(2), pages 601-631, May.
    9. Chia-Wei Kuo & Hyun-Soo Ahn & Göker Aydın, 2011. "Dynamic Pricing of Limited Inventories When Customers Negotiate," Operations Research, INFORMS, vol. 59(4), pages 882-897, August.
    10. Ødegaard, Fredrik & Wilson, John G., 2016. "Dynamic pricing of primary products and ancillary services," European Journal of Operational Research, Elsevier, vol. 251(2), pages 586-599.
    11. Oliveira, Beatriz Brito & Carravilla, Maria Antónia & Oliveira, José Fernando, 2017. "Fleet and revenue management in car rental companies: A literature review and an integrated conceptual framework," Omega, Elsevier, vol. 71(C), pages 11-26.
    12. Shanshan Hu & Xing Hu & Qing Ye, 2017. "Optimal Rebate Strategies Under Dynamic Pricing," Operations Research, INFORMS, vol. 65(6), pages 1546-1561, December.
    13. Guillermo Gallego & Michael Z. F. Li & Yan Liu, 2020. "Dynamic Nonlinear Pricing of Inventories over Finite Sales Horizons," Operations Research, INFORMS, vol. 68(3), pages 655-670, May.
    14. Ming Chen & Zhi-Long Chen, 2018. "Robust Dynamic Pricing with Two Substitutable Products," Manufacturing & Service Operations Management, INFORMS, vol. 20(2), pages 249-268, May.
    15. Weaver, Robert D. & Moon, Yongma, 2020. "Pricing Perishables: Robust Price Assurance," International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 11(01), January.
    16. Kuo, Chia-Wei & Huang, Kwei-Long, 2012. "Dynamic pricing of limited inventories for multi-generation products," European Journal of Operational Research, Elsevier, vol. 217(2), pages 394-403.
    17. Yongbo Xiao & Jian Chen, 2014. "Evaluating the potential effects from probabilistic selling of similar products," Naval Research Logistics (NRL), John Wiley & Sons, vol. 61(8), pages 604-620, December.
    18. Yalç{i}n Akçay & Harihara Prasad Natarajan & Susan H. Xu, 2010. "Joint Dynamic Pricing of Multiple Perishable Products Under Consumer Choice," Management Science, INFORMS, vol. 56(8), pages 1345-1361, August.
    19. Jørgensen, Steffen & Zaccour, Georges, 2019. "Optimal pricing and advertising policies for a one-time entertainment event," Journal of Economic Dynamics and Control, Elsevier, vol. 100(C), pages 395-416.
    20. Doan, Xuan Vinh & Lei, Xiao & Shen, Siqian, 2020. "Pricing of reusable resources under ambiguous distributions of demand and service time with emerging applications," European Journal of Operational Research, Elsevier, vol. 282(1), pages 235-251.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:244:y:2015:i:2:p:637-647. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.