Skip to main content

Context-aware Composition of Semantic Web Services


Service-based systems are usually conceived and executed in highly dynamic environments, characterized by complex and continuously evolving users’ requirements and surrounding conditions. To address this dynamicity, these systems should be designed keeping in mind the different execution contexts where they could be used. This typically impacts service discovery and composition with the aim of dynamically forging the system behavior better fitting a given context. This paper proposes a design approach based on a semantic model for context representation. It is an extension of the OWL-S ontology aimed at enriching the expressiveness of each section of a typical OWL-S semantic service description, by means of context conditions and adaptation rules. By having access to continuously updated context information, these descriptions can be exploited by a discovery/composition tool to automatically find the atomic or composite services that can be better-tuned to the requestor’s behaviors and to the particular situations of the surrounding environment.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7








  1. Akogrimo: Access to knowledge through the grid in a mobile world. Last checked: February 2014

  2. Abowd GD, Dey AK, Brown PJ, Davies N, Smith M, Steggles P (1999) Towards a better understanding of context and context-awareness. In: Proceedings of the 1st International Symposium on Handheld and Ubiquitous Computing, HUC ’99. Springer-Verlag, London, pp 304–307

    Google Scholar 

  3. Athanasopoulos D, Zarras AV, Issarny V, Pitoura E, Vassiliadis P (2008) Cowsami: interface-aware context gathering in ambient intelligence environments. Pervasive Mob Comput 4(3):360–389. doi:10.1016/j.pmcj.2007.12.004

    Article  Google Scholar 

  4. Bevilacqua L, Furno A, di Carlo V, Zimeo E (2011) A tool for automatic generation of ws-bpel compositions from owl-s described services. In: 2011 5th International Conference on Software, Knowledge Information, Industrial Management and Applications (SKIMA), pp 1–8. doi:10.1109/SKIMA.2011.6090024

  5. Bevilacqua L, Furno A, di Carlo V, Zimeo E (2012) Automatic generation of concrete compositions in adaptive contexts [to appear]. Mediterr J Comput Netw

  6. Blum AL, Furst ML (1995) Fast planning through planning graph analysis. Artif Intell 90(1):1636–1642

    Google Scholar 

  7. Bolchini C, Curino CA, Orsi G, Quintarelli E, Rossato R, Schreiber FA, Tanca L (2009) And what can context do for data?Commun ACM 52(11):136–140. doi:10.1145/1.592761.1592793

    Article  Google Scholar 

  8. Chen I, Yang S, Zhang J (2006) Ubiquitous provision of context aware web services. In: Services Computing, 2006. IEEE International Conference on SCC ’06, pp 60–68

  9. Ghallab M, Isi CK, Penberthy S, Smith DE, Sun Y, Weld D (1998) PDDL - the planning domain definition language. Tech. rep., CVC TR-98-003/DCS TR-1165, Yale Center for Computational Vision and Control. doi:

  10. Hafiddi H, Baidouri H, Nassar M, Kriouile A (2012) An aspect based pattern for context-awareness of services. Int J Comput Sci Netw Secur 12(1):71–78

    Google Scholar 

  11. Li L, Liu D, Bouguettaya A (2011) Semantic based aspect-oriented programming for context-aware web service composition. Inf Syst 36(3):551–564. doi:10.1016/

    Article  Google Scholar 

  12. Maamar Z, Benslimane D, Narendra NC (2006) What can context do for web services? Commun ACM 49(12):98–103. doi:10.1145/1.183236.1183238

    Article  Google Scholar 

  13. Pascoe J (1998) Adding generic contextual capabilities to wearable computers. In: Wearable Computers, 1998. 2nd International Symposium on Digest of Papers. pp 92–99. doi:10.1109/ISWC.1998.729534

  14. Pellier D (2011) PDDL4J. Last checked: February 2014

  15. Polese M, Tretola G, Zimeo E (2010) Self-adaptive management of web processes. In: 2010 12th IEEE International Symposium on Web Systems Evolution (WSE), pp 33–42. doi:10.1109/WSE.2010.5623573

  16. Rasch K, Li F, Sehic S, Ayani R, Dustdar S (2011) Context-driven personalized service discovery in pervasive environments. World Wide Web 14:295–319

    Article  Google Scholar 

  17. Schilit B, Adams N, Want R (1994) Context-aware computing applications. In: Proceedings of the 1994 First Workshop on Mobile Computing Systems and Applications, WMCSA ’94. IEEE Computer Society, Washington, pp 85–90. doi:10.1109/WMCSA.1994.16

    Google Scholar 

  18. Tretola G, Zimeo E (2010) Autonomic internet-scale workflows. In: Proceedings of the 3rd International Workshop on Monitoring, Adaptation and Beyond, MONA ’10. ACM, New York, pp 48–56. doi:10.1145/1.929566.1929573

    Book  Google Scholar 

  19. Truong HL, Dustdar S (2009) A survey on context-aware web service systems. Int J Web Inf Syst 5(1):5–31. doi:10.1108/17440080910947295

    Article  Google Scholar 

  20. Xiao H, Zou Y, Ng J, Nigul L (2010) An approach for context-aware service discovery and recommendation. In: 2010 IEEE International Conference on Web Services (ICWS), pp 163–170. doi:10.1109/ICWS.2010.95

  21. Zhou J, Gilman E, Palola J, Riekki J, Ylianttila M, Sun J (2011) Context-aware pervasive service composition and its implementation. Personal Ubiquitous Comput 15(3):291–303. doi:10.1007/s00779-010-0333-5

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations


Corresponding author

Correspondence to Angelo Furno.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Furno, A., Zimeo, E. Context-aware Composition of Semantic Web Services. Mobile Netw Appl 19, 235–248 (2014).

Download citation

  • Published:

  • Issue Date:

  • DOI:


  • Context-aware computing
  • Context modeling
  • Semantic Web Services
  • Service design
  • Service discovery
  • Service composition