Skip to main content
SpringerLink
Log in

New Approach for Optimal Semantic-Based Context-Aware Cloud Service Composition for ERP

  • Research Paper
  • Published:
New Generation Computing Aims and scope Submit manuscript

Abstract

Nowadays, the cloud technology has been widely accepted by enterprises. It leverages provides high-level management of expensive IT resources and several advanced techniques for developing quality IT solutions. Small and medium enterprises (SMEs) are looking for best the preeminent customized cloud enterprise resource planning (ERP) to automate wisely their business activities. Therefore, the increasing need of flexible ERP business process from heterogeneous cloud services which carried out on cost and time benefits becomes a major concern. This is very helpful to answer the required evolutions of different functional and non-functional SMEs needs (i.e., quality context-aware constraints and preferences). The existing cloud ERP systems (SAP, Oracle, etc.) as SaaS models are not flexible enough to support the ERP business process auto-adaptation. This paper aims to provide a relevant ERP business process as a composite service-targeted customer needs and context changes using semantic-based context-aware selection and optimal cloud service composition. To this end, we have proposed CxQSCloudSERP-based system ontology. It is a novel ontology for semantic describing and driving the end-to-end ERP building process. By providing the functional needs, the system generates automatically an optimal virtual ERP business process. A two-stage algorithm for context-aware services composition is proposed to obtain optimal-customized concrete ERP business process. The first stage is used to select relevant composite services that respect customer’s constraints. The second one is used to select a single optimal solution from the outcome of the first stage according to the customer’s preferences. To illustrate our approach, we have presented a prototype which gives a great flexibility to respect the enterprise’s global quality priorities. The experimental results show the efficiency and the enhanced accuracy of the proposed approach.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20

Similar content being viewed by others

References

  1. Asghari, S., Navimipour, N.J.: Review and comparison of meta-heuristic algorithms for service composition in cloud computing. Majlesi J. Multimed. Process. 4(4), 1–7 (2016)

    Google Scholar 

  2. Yao, Y., Chen, H.: Qos-aware service composition using nsga-ii 1. In: Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human, pp. 358–363. ACM (2009)

  3. Chen, C.S., Liang, W.Y., Hsu, H.Y.: A cloud computing platform for ERP applications. Appl. Soft Comput. 27, 127–136 (2015)

    Article  Google Scholar 

  4. Sasikaladevi, N., Arockiam, L.: Genetic approach for service selection problem in composite web service. Int. J. Comput. Appl. 44(4), 22–29 (2012)

    Google Scholar 

  5. Karimi, M.B., Isazadeh, A., Rahmani, A.M.: Qos-aware service composition in cloud computing using data mining techniques and genetic algorithm. J. Supercomput. 73(4), 1387–1415 (2017)

    Article  Google Scholar 

  6. Ye, Z., Zhou, X., Bouguettaya, A.: Genetic algorithm based qos-aware service compositions in cloud computing. In: Database Systems for Advanced Applications, pp. 321–334. Springer, Berlin (2011)

    Chapter  Google Scholar 

  7. Li, L., Cheng, P., Ou, L., Zhang, Z.: Applying multi-objective evolutionary algorithms to qos-aware web service composition. International Conference on Advanced Data Mining and Applications, pp. 270–281. Springer (2010)

  8. Wada, H., Champrasert, P., Suzuki, J., Oba, K.: Multiobjective optimization of sla-aware service composition. In: Services-Part I, 2008. IEEE Congress on, pp. 368–375. IEEE (2008)

  9. Taboada, H., Espiritu, J., Coit, D.: Moms-ga: a multi-objective multistate genetic algorithm for system reliability optimization design problems. IEEE Trans. Reliab. 57(1), 182–191 (2008)

    Article  Google Scholar 

  10. Jun, L., Weihua, G.: An environment-aware particle swarm optimization algorithm for services composition. In: Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on, pp. 1–4. IEEE (2009)

  11. Jula, A., Zalinda, O., Sundararajan, E.: A hybrid imperialist competitive-gravitational attraction search algorithm to optimize cloud service composition. In: Memetic Computing (MC), 2013 IEEE Workshop on, pp. 37–43. IEEE (2013)

  12. Lotfi, S. Mowlani, K.: Ica-wss: a qos-aware imperialist competitive algorithm for web service selection. In: International Conference on Informatics Engineering and Information Science, pp. 135–148. Springer (2011)

  13. Yu, Q., Chen, L., Li, B.: Ant colony optimization applied to web service compositions in cloud computing. Comput. Electr. Eng. 41, 18–27 (2015)

    Article  Google Scholar 

  14. Pop, C.B., Vlad, M., Chifu, V.R., Salomie, I., Dinsoreanu, M.: A tabu search optimization approach for semantic web service composition. In: Parallel and Distributed Computing (ISPDC), 2011 10th International Symposium on, pp. 274–277. IEEE (2011)

  15. Reffad, H., Alti, A., Roose, P.: Cloud-based semantic platform for dynamic management of context-aware mobile erp applications. In: Proceedings of the 8th International Conference on Management of Digital EcoSystems, pp. 181–188. ACM (2016)

  16. Deng, S., Huang, L., Wu, H., Wu, Z.: Constraints-driven service composition in mobile cloud computing. In: Web Services (ICWS), 2016 IEEE International Conference on, pp 228–235. IEEE (2016)

  17. Ben Hassine, A., Matsubara, S., Ishida, T.: A constraint-based approach to horizontal web service composition. In: International semantic Web conference, vol. 4273, pp. 130–143. Springer (2006)

  18. Li, J., Zheng, X.L., Chen, S.T., Song, W.W., Chen, D.: An efficient and reliable approach for quality-of-service-aware service composition. Inf. Sci. 269, 238–254 (2014)

    Article  Google Scholar 

  19. Rosenberg, F., Leitner, P., Michlmayr, A., Celikovic, P., Dustdar, S.: Towards composition as a service-a quality of service driven approach. In: Data Engineering, 2009. ICDE’09. IEEE 25th International Conference on, pp. 1733–1740. IEEE (2009)

  20. Di Martino, B., Cretella, G., Esposito, A.: Cloud services composition through cloud patterns: a semantic-based approach. Soft. Comput. 21(16), 4557–4570 (2017)

    Article  Google Scholar 

  21. Lecue, F., Mehandjiev, N.: Towards scalability of quality driven semantic web service composition. In: Web Services, 2009. ICWS 2009. IEEE International Conference on, pp. 469–476. IEEE (2009)

  22. Alti, A., Laborie, S., Roose, P.: Dynamic semantic-based adaptation of multimedia documents. Trans. Emerg. Telecommun. Technol. 25(2), 239–258 (2014)

    Article  Google Scholar 

  23. Johansson, B., Ruivo, P.: Exploring factors for adopting ERP as saas. Proc. Technol. 9, 94–99 (2013)

    Article  Google Scholar 

  24. Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: Nsga-ii. IEEE Trans. Evol. Comput. 6(2), 182–197 (2002)

    Article  Google Scholar 

  25. Zhang, K.J., Dong, P.J., Ma, B., Tang, B.Y., Cai, H.: Innovation of it service in textile industrial clusters from the service system perspective. In: Logistics Systems and Intelligent Management, 2010 International Conference on, vol. 3, pp. 1819–1822. IEEE (2010)

  26. Ranganathan, C., Teo, T.S.H., Dhaliwal, J.: Web-enabled supply chain management: key antecedents and performance impacts. Int. J. Inf. Manag. 31(6), 533–545 (2011)

    Article  Google Scholar 

  27. Tari, K., Amirat, Y. Chibani, A., Yachir, A., Mellouk, A.: Context-aware dynamic service composition in ubiquitous environment. In: Communications (ICC), 2010 IEEE International Conference on, pp. 1–6. IEEE (2010)

  28. Khurana, R., Bawa, K.R.: Quality based cloud service broker for optimal cloud service provider selection. Int. J. Appl. Eng. Res. 12(18), 7962–7975 (2017)

    Google Scholar 

  29. Tarantilis, C.D., Kiranoudis, C.T., Theodorakopoulos, N.D.: A web-based ERP system for business services and supply chain management: application to real-world process scheduling. Eur. J. Oper. Res. 187(3), 1310–1326 (2008)

    Article  Google Scholar 

  30. Netbeans. https://netbeans.org/. Accessed 21 Oct 2017

  31. Horrocks, I., Patel-Schneider, P.F., Boley, H., Tabet, S., Grosof, B., Dean, M. et al: Swrl: a semantic web rule language combining owl and ruleml. W3C Memb. Submiss. 21, 79 (2004)

  32. Prud, E., Seaborne, A. et al: Sparql query language for rdf. http://www.w3.org/TR/rdf-sparql-query/ (2006). Accessed 17 Oct 2017

  33. Zeleny, M.: Multiple Criteria Decision Making. Mcgraw-Hill, New York (1982)

    MATH  Google Scholar 

  34. Li, B., Li, M.: Research and design on the refinery ERP and EERP based on SOA and the component oriented technology. In: Networking and Digital Society, 2009. ICNDS’09. International Conference on, vol. 1, pp. 85–88. IEEE (2009)

  35. Gollakota, K.: Ict use by businesses in rural india: the case of eid parry’s indiagriline. Int. J. Inf. Manag. 28(4), 336–341 (2008)

    Article  Google Scholar 

  36. Protégé. http://protege.stanford.edu. Accessed 8 Sept 2017

  37. Mital, M., Pani, A., Ramesh, R.: Determinants of choice of semantic web based software as a service: an integrative framework in the context of e-procurement and ERP. Comput. Ind. 65(5), 821–827 (2014)

    Article  Google Scholar 

  38. Martin, D., Burstein, M., Hobbs, J., Lassila, O., McDermott, D., McIlraith, S., Sirin, E.: OWL-S: semantic markup for web services. W3C Memb. Submiss. 22(4), 1–38 (2004)

    Google Scholar 

  39. Huang, X., Lei, X., Jiang, Y.: Comparison of three multi-objective optimization algorithms for hydrological model. In: Computational Intelligence and Intelligent Systems, pp. 209–216, Springer, Berlin (2012)

    Google Scholar 

  40. Qin, Y.: Toward unified cloud service discovery for enhanced service identification. In: Service Research and Innovation: 5th and 6th Australasian Symposium, ASSRI 2015 and ASSRI 2017, Sydney, NSW, Australia, November 2–3, 2015, and October 19–20, 2017

Download references

Author information

Authors and Affiliations

  1. LAS Laboratory, University of Ferhat Abbas Setif-1, Sétif, Algeria

    Hamza Reffad

  2. LRSD Laboratory, University of Ferhat Abbas Setif-1, Sétif, Algeria

    Adel Alti

Authors
  1. Hamza Reffad
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Adel Alti
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hamza Reffad.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Reffad, H., Alti, A. New Approach for Optimal Semantic-Based Context-Aware Cloud Service Composition for ERP. New Gener. Comput. 36, 307–347 (2018). https://doi.org/10.1007/s00354-018-0036-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00354-018-0036-4

Keywords

Search

Navigation