Skip to main content

Cost-Driven Cloud Service Recommendation for Building E-Commerce Websites

  • Conference paper
  • First Online:
New Trends in Computer Technologies and Applications (ICS 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1013))

Included in the following conference series:

  • 1333 Accesses

Abstract

With the evolution of software engineering technology, using cloud services to replace self-built information systems has been proven an economical and reliable way. However, how to help e-commerce service system builders to choose suitable compositions of cloud services that meet their needs is still a challenge. In the past decade, a number of academic studies have explored the selection strategies and algorithms for cloud services, however, most efforts are not able to consider multiple types of cloud services simultaneously to provide composite cloud service solutions. To address the above issue, this study proposes a cost-driven recommendation method, called ECSSR (E-Commerce Service Suite Recommendation). ECSSR takes the user budget as the core factor and simultaneously considers the user’s preferences for the service types. A prototype system, referred to as ECClouder, is also designed and implemented to realize the features of ECSSR. ECClouder is able to collect the user’s requirements, convert application-level requirements into infrastructure-level requirements, and produce appropriate cloud service solutions. The case study show that ECClouder can effectively help users to find cloud service solutions that are reasonably priced and meet their needs.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
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

Notes

  1. 1.

    https://sourceforge.net/projects/freemind/.

  2. 2.

    https://jsoup.org/.

  3. 3.

    http://dashboard.ecclouder.com/.

References

  1. Saaty, T.L.: Decision Making for Leaders-The Analytic Hierarchy Process for Decisions in a Complex World. RWS Publications, Pittsburgh (1990)

    Google Scholar 

  2. Goh, C.H., Tung, Y.-C.A., Cheng, C.H.: A revised weighted sum decision model for robot selection. Comput. Ind. Eng. 30, 193–199 (1996)

    Article  Google Scholar 

  3. Sun, L., Dong, H., Hussain, F.K., Hussain, O.K., Chang, E.: Cloud service selection state-of-the-art and future research directions. J. Netw. Comput. Appl. 45, 134–150 (2014)

    Article  Google Scholar 

  4. Karim, R., Ding, C., Miri, A.: An end-to-end QoS mapping approach for cloud service selection. In: IEEE Ninth World Congress on Services (2013)

    Google Scholar 

  5. Lee, S., Seo, K.-K.: A hybrid multi-criteria decision-making model for a cloud service selection problem using BSC, fuzzy delphi method and fuzzy AHP. Wirel. Pers. Commun. 86, 57–75 (2016)

    Article  Google Scholar 

  6. Garg, S.K., Versteeg, S., Buyya, R.: SMICloud: a framework for comparing and ranking of cloud services. In: Fourth IEEE International Conference on Utility and Cloud Computing (2011)

    Google Scholar 

  7. Menzel, M., Ranjan, R.: CloudGenius: decision support for web server cloud migration. ACM (2012)

    Google Scholar 

  8. Lo, C.-C., Chen, D.-Y., Tsai, C.-F., Chao, K.-M.: Service Selection based on fuzzy TOPSIS method. In: 2010 IEEE 24th International Conference on Advanced Information Networking and Applications Workshops (WAINA) (2010)

    Google Scholar 

  9. Zhang, X., Dou, W.: Preference-aware QoS evaluation for cloud web service composition based on artificial neural networks. In: Wang, F.L., Gong, Z., Luo, X., Lei, J. (eds.) WISM 2010, vol. 6318, pp. 410–417. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-16515-3_51

    Chapter  Google Scholar 

  10. Tajvidi, M., Ranjan, R., Kolodziej, J., Wang, L.: Fuzzy cloud service selection framework. In: IEEE 3rd International Conference on Cloud Networking (CloudNet) (2014)

    Google Scholar 

  11. Chen, G., Bai, X., Huang, X., Li, M., Zhou, L.: Evaluating services on the cloud using ontology QoS model. In: 2011 IEEE 6th International Symposium on Service Oriented System Engineering (SOSE) (2011)

    Google Scholar 

  12. Oh, S.H., La, H.J., Kim, S.D.: A reusability evaluation suite for cloud services. In: 2011 IEEE 8th International Conference on e-Business Engineering (ICEBE) (2011)

    Google Scholar 

  13. Govil, S.B., Thyagarajan, K., Srinivasan, K., Chaurasiya, V.K., Das, S.: An approach to identify the optimal cloud in cloud federation. J. Cloud Comput. Serv. Sci. 1(1), 35–44 (2012)

    Google Scholar 

  14. Qu, L., Wang, Y., Orgun, M.A., Liu, L., Liu, H., Bouguettaya, A.: CCCloud: context-aware and credible cloud service selection based on subjective assessment and objective assessment. IEEE Trans. Serv. Comput. 8(3), 369–383 (2015)

    Article  Google Scholar 

  15. Ghosh, N., Ghosh, S.K., Das, S.K.: SelCSP: a framework to facilitate selection of cloud service providers. IEEE Trans. Cloud Comput. 3, 66–79 (2015)

    Article  Google Scholar 

  16. Khurana, R., Bawa, R.K.: QoS based cloud service selection paradigms. In: 2016 6th International Conference - Cloud System and Big Data Engineering (Confluence) (2016)

    Google Scholar 

  17. Uchibayashi, T., Apduhan, B., Shiratori, N.: Towards a cloud ontology clustering mechanism to enhance IaaS service discovery and selection. In: Gervasi, O., et al. (eds.) ICCSA 2015. LNCS, vol. 9155, pp. 545–556. Springer, Cham (2015)

    Google Scholar 

  18. Baranwal, G., Vidyarthi, D.P.: A framework for selection of best cloud service provider using ranked voting method. In: 2014 IEEE International Advance Computing Conference (IACC) (2014)

    Google Scholar 

  19. Roussey, C., Pinet, F., Kang, M.A., Corcho, O.: An introduction to ontologies and ontology engineering. In: Falquet, G., Métral, C., Teller, J., Tweed, C. (eds.) Ontologies in Urban Development Projects. Advanced Information and Knowledge Processing, vol. 1, pp. 9–38. Springer, London (2011). https://doi.org/10.1007/978-0-85729-724-2

    Chapter  Google Scholar 

Download references

Acknowledgments

This research was sponsored by Ministry of Science and Technology in Taiwan under the grant MOST 105-2221-E-019-054-MY3.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Shang-Pin Ma .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Wang, CY., Ma, SP., Dai, SH. (2019). Cost-Driven Cloud Service Recommendation for Building E-Commerce Websites. In: Chang, CY., Lin, CC., Lin, HH. (eds) New Trends in Computer Technologies and Applications. ICS 2018. Communications in Computer and Information Science, vol 1013. Springer, Singapore. https://doi.org/10.1007/978-981-13-9190-3_80

Download citation

  • DOI: https://doi.org/10.1007/978-981-13-9190-3_80

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9189-7

  • Online ISBN: 978-981-13-9190-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics