Towards a Fuzzy-oriented Framework for Service Selection in Cloud e-Marketplaces

Azubuike Ezenwoke, Olawande Daramola, Matthew Adigun

2017

Abstract

The growing popularity of cloud services requires service selection platforms that offer enhanced user experience in terms of handling complex user requirements, elicitation of quality of service (QoS) requirements, and presentation of search results to aid decision making. So far, none of the existing cloud service selection approaches has provided a framework that wholly possesses these attributes. In this paper, we proposed a fuzzy-oriented framework that could facilitate enhanced user experience in cloud e-marketplaces through formal composition of atomic services to satisfy complex user requirements, elicitation and processing of subjective user QoS requirements, and presentation of search results in a visually intuitive way that aids users’ decision making. To do this, an integration of key concepts such as constrained-based reasoning on feature models, fuzzy pairwise comparison of QoS attributes, fuzzy decision making, and information visualization have been used. The applicability of the framework is illustrated with an example of Customer Relationship Management as a Service.

References

  1. Akolkar, R., Chefalas, T., Laredo, J., Peng, C.-S., Sailer, A., Schaffa, F., Silva-Lepe, I.a. and Tao, T., 2012. The Future of Service Marketplaces in the Cloud. In IEEE 8th World Congress on Services, pages 262-269.
  2. Beets, S. and Wesson, J. (2011). Using information visualization to support web service discovery. In SAICSIT, pages 11-20.
  3. Bellman, R. and Zadeh, L. (1970). Decision making in fuzzy environment. MonogemenlScience. 141-164.
  4. Benavides, D., Segura, S. and Ruiz-Cortes, A. (2010). Automated analysis of feature models 20 years later: A literature review. Information Systems. 615-636.
  5. Berger, T., Pfeiffer, R.-H., Tartler, R., Dienst, S., Czarnecki, K., Wasowski, A. and She, S. (2014) Variability Mechanisms in Software Ecosystems. Information and Software Technology, 56(11):1520- 1535.
  6. Buckley, J. (1985) Fuzzy hierarchical analysis. Fuzzy Sets and Systems, 233-247.
  7. Esposito, C., Ficco, M., Palmieri, F. and Castiglione, A. (2015). Smart Cloud Storage Service Selection Based on Fuzzy Logic, Theory of Evidence and Game Theory. In IEEE Transactions on Computers, Available: 0018-9340.
  8. Ezenwoke, A., (2017). Using constraint reasoning on feature models to populate ecosystem-driven cloud services e-marketplace. Covenant University Technical Report.[Online]. Available at: eprints.covenantuniversity.edu.ng/7624/
  9. Gatzioura, A., Menychtas, A., Moulos, V. and Varvarigou, T. (2012). Incorporating Business Intelligence in Cloud Marketplaces. In IEEE 10th International Symposium on Parallel and Distributed Processing with Applications, pages 466-472.
  10. Millet, I. (1997). The effectiveness of alternative preference elicitation methods in the analytic hierarchy process, Journal of Multi-Criteria Decision Analysis, 41-51.
  11. Mirmotalebi, R., Ding, C. and Chi, C. (2012). Modeling User's Non-functional Preferences for Personalized Service Ranking. Service-Oriented Computing.
  12. Mohabbati, B., Gaševic, D., Hatala, M., Asadi, M., Bagheri, E. and Boškovic, M. (2011). A Quality Aggregation Model for Service-Oriented Software Product Lines Based on Variability and Composition Patterns. Service-Oriented Computing, 436-451.
  13. Qu, C. and Buyya, R. (2014). A Cloud Trust Evaluation System using Hierarchical Fuzzy Inference System for Service Selection. In 28th International Conference on Advanced Information Networking and Applications, pages 850-857.
  14. Rehman, Z, Hussain, F. and Hussainz, O. (2011). Towards Multi-Criteria Cloud Service Selection. In 5th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, pages 44- 48.
  15. Spence, R. (2014). Information visualization: An introduction, 3rd edition, Springer.
  16. Wittern, E., Kuhlenkamp, J. and Menzel, M. (2012). Cloud Service Selection Based on Variability Modeling. Service-Oriented Computing, 127-141.
  17. Yu, Z. and Zhang, L. (2014). QoS-aware SaaS Services Selection with Interval Numbers for Group User. Journal of Software. 553-559.
  18. Zadeh, L.A. (1974). The concept of a linguistic variable and its application to Approximate Reasoning. Learning systems and intelligent robots, 1-10.
Download


Paper Citation


in Harvard Style

Ezenwoke A., Daramola O. and Adigun M. (2017). Towards a Fuzzy-oriented Framework for Service Selection in Cloud e-Marketplaces . In Proceedings of the 7th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER, ISBN 978-989-758-243-1, pages 632-637. DOI: 10.5220/0006365306320637


in Bibtex Style

@conference{closer17,
author={Azubuike Ezenwoke and Olawande Daramola and Matthew Adigun},
title={Towards a Fuzzy-oriented Framework for Service Selection in Cloud e-Marketplaces},
booktitle={Proceedings of the 7th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,},
year={2017},
pages={632-637},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006365306320637},
isbn={978-989-758-243-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,
TI - Towards a Fuzzy-oriented Framework for Service Selection in Cloud e-Marketplaces
SN - 978-989-758-243-1
AU - Ezenwoke A.
AU - Daramola O.
AU - Adigun M.
PY - 2017
SP - 632
EP - 637
DO - 10.5220/0006365306320637