Skip to main content
SpringerLink
Log in

A Framework for Cost-Aware Cloud Data Management

  • Conference paper
On the Move to Meaningful Internet Systems: OTM 2012 (OTM 2012)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7565))

Abstract

The emerging world of offering information services through the cloud necessitates the coalescence of existing research and business technologies into the provision of all-inclusive solutions for data management. This paper proposes a framework that can support cost-aware data management in the cloud. Users and cloud providers can use the framework to receive and provide services that comply with agreements on data service cost and requirements and allow for profit while being efficient in terms of performance. The proposed framework includes modules that incorporate the notion of monetary cost in current data management, but also modules that take optimization decisions for future data management taking into account both monetary cost and performance. The framework dictates the design of a middleware application that can be plugged on top of a cloud data management system. Such a middleware receives the user’s workload and preferences for cost and query performance and controls data management so that the user is satisfied and the cloud provider is viable and, furthermore, profitable. An initial realization of part of the framework as a middleware application has already been constructed, tested and published with promising results.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. http://aws.amazon.com/ec2

  2. http://www.gogrid.com

  3. http://code.google.com/appengine

  4. Dash, D., Kantere, V., Ailamaki, A.: An Economic Model for Self-Tuned Cloud Caching. In: ICDE, pp. 1687–1693 (2009)

    Google Scholar 

  5. Kantere, V., Dash, D., Gratsias, G., Ailamaki, A.: Predicting cost amortization for query services. In: ACM SIGMOD, pp. 325–336 (2011)

    Google Scholar 

  6. Kantere, V., Dash, D., Francois, G., Kyriakopoulou, S., Ailamaki, A.: Optimal Pricing for a Cloud Cache. The IEEE TKDE, Special Issue on Cloud Data Management 23(6), 1345–1358 (2011)

    Google Scholar 

  7. Ramaswamy, L., Liu, L., Iyengar, A.: Cache clouds: Cooperative caching of dynamic documents in edge networks. In: ICDCS, pp. 229–238 (2005)

    Google Scholar 

  8. Ramaswamy, L., Liu, L., Iyengar, A.: Scalable delivery of dynamic content using a cooperative edge cache grid. IEEE TKDE 19(5) (2007)

    Google Scholar 

  9. Bhattacharjee, S., Calvert, K.L., Zegura, E.W.: Self-organizing wide-area network caches. In: IEEE Infocom, pp. 752–757 (1998)

    Google Scholar 

  10. Malik, T., Burns, R.C., Chaudhary, A.: Bypass caching: Making scientific databases good network citizens. In: ICDE, pp. 94–105 (2005)

    Google Scholar 

  11. Wang, X., Burns, R.C., Terzis, A., Deshpande, A.: Network-aware join processing in global-scale database federations. In: ICDE, pp. 586–595 (2008)

    Google Scholar 

  12. Foster, I.: What is the grid? a three point checklist (2002), http://www-fp.mcs.anl.gov/foster/articles/whatisthegrid.pdf

  13. Nieto-Santisteban, M.A., Gray, J., Szalay, A.S., Annis, J., Thakar, A.R., Omullane, W.J.: When database systems meet the grid. In: CIDR, pp. 154–161 (2005)

    Google Scholar 

  14. Watson, P.: Databases and the grid. Grid Computing: Making The Global Infrastructure a Reality, Technical Report (2001)

    Google Scholar 

  15. Stonebraker, M., Aoki, P.M., Litwin, W., Pfeffer, A., Sah, A., Sidell, J., Staelin, C., Yu, A.: Mariposa: A wide-area distributed database system. VLDB J. 5(1) (1996)

    Google Scholar 

  16. Wellman, M.P., Walsh, W.E., Wurman, P.R., Mackie-Mason, J.K.: Auction protocols for decentralized scheduling. Games and Economic Behavior 35, 2001 (1998)

    MathSciNet  Google Scholar 

  17. Ernemann, C., Hamscher, V., Yahyapour, R.: Economic Scheduling in Grid Computing. In: Feitelson, D.G., Rudolph, L., Schwiegelshohn, U. (eds.) JSSPP 2002. LNCS, vol. 2537, pp. 128–152. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  18. Moreno, R., Alonso-Conde, A.B.: Job Scheduling and Resource Management Techniques in Economic Grid Environments. In: Fernández Rivera, F., Bubak, M., Gómez Tato, A., Doallo, R. (eds.) Across Grids 2003. LNCS, vol. 2970, pp. 25–32. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  19. Kradolfer, M., Tombros, D.: Market-based workflow management. International Journal of Cooperative Information Systems 7 (1998)

    Google Scholar 

  20. Chen, C., Maheswaran, M., Toulouse, M.: Supporting co-allocation in an auctioning-based resource allocator for grid systems. In: IPDPS, pp. 89–96 (2002)

    Google Scholar 

  21. The Office of Science Data-Management Challenge. Report from the DOE Office of Science Data-Management Workshops (March-May 2004)

    Google Scholar 

  22. Ailamaki, A., Kantere, V., Dash, D.: Managing scientific data. Communications of ACM 53(6), 68–78 (2010)

    Article  Google Scholar 

  23. Gray, J., Szalay, A.S., Thakar, A., Stoughton, C., van Berg, J.: Online Scientific Data Curation, Publication, and Archiving. CoRR cs.DL/0208012 (2002)

    Google Scholar 

  24. Gray, J., Liu, D.T., Nieto-Santisteban, M.A., Szalay, A.S., DeWitt, D.J., Heber, G.: Scientific Data Management in the Coming Decade. CoRR abs/cs/0502008 (2005)

    Google Scholar 

  25. Feitelson, D.G.: Locality of sampling and diversity in parallel system workloads. In: ICS, pp. 53–63 (2007)

    Google Scholar 

  26. Li, H., Groep, D.L., Wolters, L.: Workload Characteristics of a Multi-cluster Supercomputer. In: Feitelson, D.G., Rudolph, L., Schwiegelshohn, U. (eds.) JSSPP 2004. LNCS, vol. 3277, pp. 176–193. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  27. Li, H., Muskulus, M., Wolters, L.: Modeling correlated workloads by combining model based clustering and a localized sampling algorithm. In: ICS, pp. 64–72 (2007)

    Google Scholar 

  28. Minh, T.N., Wolters, L.: Modeling Parallel System Workloads with Temporal Locality. In: Frachtenberg, E., Schwiegelshohn, U. (eds.) JSSPP 2009. LNCS, vol. 5798, pp. 101–115. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  29. Minh, T.N., Wolters, L.: Modeling job arrival process with long range dependence and burstiness characteristics. In: CCGRID, pp. 324–330 (2009)

    Google Scholar 

  30. Calder, B., Grunwald, D.: Next cache line and set prediction. In: ISCA, pp. 287–296 (1995)

    Google Scholar 

  31. Lai, A.-C., Fide, C., Falsafi, B.: Dead-block prediction & dead-block correlating prefetchers. In: ISCA, pp. 144–154 (2001)

    Google Scholar 

  32. Hu, Z., Kaxiras, S., Martonosi, M.: Timekeeping in the memory system: predicting and optimizing memory behavior. In: ISCA, pp. 209–220 (2002)

    Google Scholar 

  33. Kharbutli, M., Solihin, Y.: Counter-based cache replacement and bypassing algorithms. IEEE Transactions in Computing 57(4), 433–447 (2008)

    Article  MathSciNet  Google Scholar 

  34. Sulistio, A., Kyong Hoon, K., Buyya, R.: Using revenue management to determine pricing of reservations. In: IEEE e-Science, pp. 396–405 (2007)

    Google Scholar 

  35. Allenotor, D., Thulasiram, R.K., Thulasiraman, P.: A Financial Option Based Grid Resources Pricing Model: Towards an Equilibrium between Service Quality for User and Profitability for Service Providers. In: Abdennadher, N., Petcu, D. (eds.) GPC 2009. LNCS, vol. 5529, pp. 13–24. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  36. Lin, Z., Ramanathan, S., Zhao, H.: Usage-based dynamic pricing of Web services for optimizing resource allocation. Inf. Systems and E-Business Management 3(3), 221–242 (2005)

    Article  Google Scholar 

  37. Masuda, Y., Whang, S.: Dynamic Pricing for Network Service: Equilibrium and Stability. Management Science 45(6), 857–869 (1999)

    Article  MATH  Google Scholar 

  38. Cao, X.-R., Shen, H.-X., Milito, R., Wirth, P.: Internet pricing with a game theoretical approach: concepts and examples. ACM Transactions on Networking 10(2), 208–216 (2007)

    Google Scholar 

  39. Bitran, G.R., Caldentey, R.: An overview of pricing models for revenue management. MSOM 5(3), 203–229 (2003)

    Article  Google Scholar 

  40. Ghose, A., Choudhary, V., Mukhopadhyay, T., Rajan, U.: Dynamic pricing: A strategic advantage for electronic retailers. In: ICIS, p. 28 (2003)

    Google Scholar 

  41. You, P.-S., Chen, T.C.: Dynamic pricing of seasonal goods with spot and forward purchase demands. Comput. Math. Appl. 54(4), 490–498 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  42. Gallego, G., van Ryzin, G.: Optimal Dynamic Pricing of Inventories with Stochastic Demand over Finite Horizons. Management Science 40(8), 999–1020 (1994)

    Article  MATH  Google Scholar 

  43. Schnaitter, K., Polyzotis, N., Getoor, L.: Modeling index interactions. In: VLDB, pp. 1234–1245 (2009)

    Google Scholar 

  44. http://www.sdss.org

Download references

Author information

Authors and Affiliations

  1. Cyprus University of Technology, Cyprus

    Verena Kantere

Authors
  1. Verena Kantere
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Computer Science, Semantic Technology and Application Research Laboratory (STARLab), Vrije Universiteit Brussel, Building G-10, Pleinlaan 2, 1050, Brussels, Belgium

    Robert Meersman

  2. Research Centre for Automatic Control, School of Engineering in Information Technology, University of Lorraine, CNRS, Campus scientifique, BP 70239, 54506, Vandoeuvre-les-Nancy, France

    Hervé Panetto

  3. La Trobe University, Melbourne, VIC, Australia

    Tharam Dillon

  4. Faculty of Computer Science, University of Vienna, 1010, Vienna, Austria

    Stefanie Rinderle-Ma

  5. Institute of Databases and Information Systems, Ulm University, Germany

    Peter Dadam

  6. School of Information Technology and Electrical Engineering, University of Queensland, 4072, Brisbane, QLD, Australia

    Xiaofang Zhou

  7. HP Labs, Bristol, UK

    Siani Pearson

  8. Johannes Kepler University, Linz, Austria

    Alois Ferscha

  9. Università di Modena e Reggio Emilia, Modena, Italy

    Sonia Bergamaschi

  10. ADVIS Lab, Department of Computer Science, University of Illinois at Chicago, Chicago, IL, USA

    Isabel F. Cruz

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Kantere, V. (2012). A Framework for Cost-Aware Cloud Data Management. In: Meersman, R., et al. On the Move to Meaningful Internet Systems: OTM 2012. OTM 2012. Lecture Notes in Computer Science, vol 7565. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33606-5_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-33606-5_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33605-8

  • Online ISBN: 978-3-642-33606-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation