Skip to main content
Log in

Building adaptive context-aware service-based smart systems

  • Original Research Paper
  • Published:
Service Oriented Computing and Applications Aims and scope Submit manuscript

Abstract

Existing smart systems tend to be domain specific and developed end-to-end in an ad hoc manner and thus tend to be time and resource consuming, error prone and hard to interoperate and integrate. The objective of this paper is to provide a method through which the method users can follow a general process model and a uniform set of concepts to define the main elements involved in their targeted smart solution while also thinking about how their system could or should improve, adapt and eventually integrate with other systems. We propose an approach to design smart systems based on the principles of service-oriented computing, context-awareness and adaptability to tackle the previously mentioned issues. The proposed approach, called AS3 (adaptive service-based smart systems), consists of two main contributions. To deal with the interoperability, integration and adaptability issues, we first propose a smart system loop to showcase the capabilities of smart systems, the main concepts in play and their interactions. Then, we propose a method to design smart systems that is supported by a product metamodel and a process model. The application of AS3 on a road security-focused intelligent transport system design and simulation shows its relevance and efficiency in designing adaptive smart systems.

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

Access this article

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

Instant access to the full article PDF.

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

Similar content being viewed by others

Notes

  1. SMARTROAD is a cooperation project funded by CAMPUS FRANCE [PHC TOUBKAL 2017 (French–Morocco bilateral program) Grant Number: 36804YH], which aims to create a platform, a method and a set of design tools to develop dynamically composed services in the context of smart roads.

  2. https://www.incose.org/about-systems-engineering/system-and-se-definition.

  3. https://dictionary.cambridge.org/fr/dictionnaire/anglais/situation.

  4. https://github.com/wsdream/wsdream-dataset/tree/master/dataset1.

  5. https://github.com/wsdream/wsdream-dataset/tree/master/dataset1.

  6. https://github.com/faieqs/SMRec.

  7. https://github.com/faieqs/SMRec.

References

  1. Abowd GD, Dey AK, Brown PJ, Davies N, Smith M, Steggles P (1999) Towards a better understanding of context and context-awareness. In: International symposium on handheld and ubiquitous computing. Springer, Berlin, pp 304–307

  2. Ait-Cheik-Bihi W, Nait-Sidi-Moh A, Bakhouya M, Gaber J, Wack M (2012) Transportml platform for collaborative location-based services. SOCA 6(4):363–378. https://doi.org/10.1007/s11761-012-0114-2

    Article  Google Scholar 

  3. Baresi L, Di Nitto E, Ghezzi C, Guinea S (2007) A framework for the deployment of adaptable web service compositions. SOCA 1(1):75–91. https://doi.org/10.1007/s11761-007-0004-1

    Article  Google Scholar 

  4. Bouguettaya A, Singh M, Huhns M, Sheng QZ, Dong H, Yu Q, Neiat AG, Mistry S, Benatallah B, Medjahed B, Ouzzani M, Casati F, Liu X, Wang H, Georgakopoulos D, Chen L, Nepal S, Malik Z, Erradi A, Wang Y, Blake B, Dustdar S, Leymann F, Papazoglou M (2017) A service computing manifesto: the next 10 years. Commun ACM 60(4):64–72. https://doi.org/10.1145/2983528

    Article  Google Scholar 

  5. Candillier L, Meyer F, Boullé M (2007) Comparing state-of-the-art collaborative filtering systems. In: Perner P (ed) Machine learning and data mining in pattern recognition. Springer, Berlin, pp 548–562

    Chapter  Google Scholar 

  6. Casati F, Shan MC (2001) Dynamic and adaptive composition of e-services. Inf Syst 26(3):143–163. https://doi.org/10.1016/S0306-4379(01)00014-X 12th International Conference on Advanced Systems Engineering

    Article  MATH  Google Scholar 

  7. Cela O, Cortes-Cornax M, Front A, Rieu D (2019) Methodological framework to guide the development of continual evolution methods. In: Giorgini P, Weber B (eds) Advanced information systems engineering. Springer, Cham, pp 48–63

    Chapter  Google Scholar 

  8. Chang CK, Jiang H, Ming H, Oyama K (2009) Situ: A situation-theoretic approach to context-aware service evolution. IEEE Trans Serv Comput 2(3):261–275. https://doi.org/10.1109/TSC.2009.21

    Article  Google Scholar 

  9. Chang J, Yao W, Li X (2017) The design of a context-aware service system in intelligent transportation system. Int J Distrib Sens Netw 13(10):1–18. https://doi.org/10.1177/1550147717738165

    Article  Google Scholar 

  10. Demirkan H (2013) A smart healthcare systems framework. IT Prof 15(5):38–45. https://doi.org/10.1109/MITP.2013.35

    Article  Google Scholar 

  11. Faieq S, Saidi R, Elghazi H, Rahmani MD (2017) C2iot: a framework for cloud-based context-aware internet of things services for smart cities. Procedia Comput Sci 110:151–158. https://doi.org/10.1016/j.procs.2017.06.072

    Article  Google Scholar 

  12. Faieq S, Front A, Saidi R, El Ghazi H, Rahmani MD (2019) A context-aware recommendation-based system for service composition in smart environments. SOCA 13(4):341–355. https://doi.org/10.1007/s11761-019-00277-7

    Article  Google Scholar 

  13. Fang J, Hu S, Han Y (2004) A service interoperability assessment model for service composition. In: Proceedings of IEEE international conference on services computing, 2004 (SCC 2004), pp 153–158. https://doi.org/10.1109/SCC.2004.1358002

  14. Force IRSCMT (2014) An overview report on the current status and implications of road safety & connected mobility. Tech. rep, IRU, Michelin Group

  15. Haeckel SH (1999) Adaptive enterprise: creating and leading sense-and-respond organizations. Harvard Business Press, Brighton

    Google Scholar 

  16. He P, Zhu J, Zheng Z, Xu J, Lyu MR (2014) Location-based hierarchical matrix factorization for web service recommendation. In: 2014 IEEE international conference on web services, pp 297–304. https://doi.org/10.1109/ICWS.2014.51

  17. Kephart JO, Chess DM (2003) The vision of autonomic computing. Computer 36(1):41–50. https://doi.org/10.1109/MC.2003.1160055

    Article  MathSciNet  Google Scholar 

  18. Lee H, Lee J (2018) Development concepts of smart service system-based smart factory (4SF). In: INCOSE international symposium, vol 28, no 1, pp 1153–1169. https://doi.org/10.1002/j.2334-5837.2018.00540.x

  19. Lim C, Maglio PP (2019) Clarifying the concept of smart service system. Springer, Cham, pp 349–376. https://doi.org/10.1007/978-3-319-98512-1_16

    Book  Google Scholar 

  20. Lo W, Yin J, Deng S, Li Y, Wu Z (2012) Collaborative web service QoS prediction with location-based regularization. In: 2012 IEEE 19th international conference on web services, pp 464–471. https://doi.org/10.1109/ICWS.2012.49

  21. MarsaMaestre I, Lopez-Carmona MA, Velasco JR (2008) A hierarchical, agent-based service oriented architecture for smart environments. SOCA 2(4):167–185. https://doi.org/10.1007/s11761-008-0030-7

    Article  Google Scholar 

  22. Mohsin A, Janjua NK (2018) A review and future directions of SOA-based software architecture modeling approaches for system of systems. SOCA 12(3):183–200. https://doi.org/10.1007/s11761-018-0245-1

    Article  Google Scholar 

  23. Organization WH et al (2018) Global status report on road safety 2018. World Health Organization, Geneva

    Google Scholar 

  24. Palanca J, Val Ed, Garcia-Fornes A, Billhardt H, Corchado JM, Julián V (2018) Designing a goal-oriented smart-home environment. Inf Syst Front 20(1):125–142. https://doi.org/10.1007/s10796-016-9670-x

    Article  Google Scholar 

  25. Park CY, Laskey KB, Salim S, Lee JY (2017) Predictive situation awareness model for smart manufacturing. In: 2017 20th international conference on information fusion (fusion), pp 1–8. https://doi.org/10.23919/ICIF.2017.8009849

  26. Rodrigues GS, Guimarães FP, Rodrigues GN, Knauss A, de Araújo JPC, Andrade H, Ali R (2019) Goald: a goal-driven deployment framework for dynamic and heterogeneous computing environments. Inf Softw Technol 111:159–176. https://doi.org/10.1016/j.infsof.2019.04.003

    Article  Google Scholar 

  27. Rolland C (2007) Capturing system intentionality with maps. Springer, Berlin, pp 141–158. https://doi.org/10.1007/978-3-540-72677-7_9

    Book  Google Scholar 

  28. Santana EFZ, Chaves AP, Gerosa MA, Kon F, Milojicic DS (2018) Software platforms for smart cities: Concepts, requirements, challenges, and a unified reference architecture. ACM Comput Surv (CSUR) 50(6). https://doi.org/10.1145/3124391

  29. Santofimia MJ, Villa D, Aceña O, del Toro X, Trapero C, Villanueva FJ, Lopez JC (2018) Enabling smart behavior through automatic service composition for internet of things-based smart homes. Int J Distrib Sens Netw 14(8)

  30. Sedhain S, Menon AK, Sanner S, Xie L (2015) Autorec: autoencoders meet collaborative filtering. In: Proceedings of the 24th international conference on world wide web. ACM, pp 111–112

  31. Sivamani S, Bae N, Cho Y (2013) A smart service model based on ubiquitous sensor networks using vertical farm ontology. Int J Distrib Sens Netw 9(12). https://doi.org/10.1155/2013/161495

  32. Sun H, Zheng Z, Chen J, Lyu MR (2013) Personalized web service recommendation via normal recovery collaborative filtering. IEEE Trans Serv Comput 6(4):573–579. https://doi.org/10.1109/TSC.2012.31

    Article  Google Scholar 

  33. Tang M, Jiang Y, Liu J, Liu X (2012) Location-aware collaborative filtering for QoS-based service recommendation. In: 2012 IEEE 19th international conference on web services, pp 202–209. https://doi.org/10.1109/ICWS.2012.61

  34. Villa D, Aceña O, Villanueva FJ, Santofimia MJ, Escolar S, del Toro Garca X, Lopez JC (2017) IDM: an inter-domain messaging protocol for IoT. In: IECON 2017—43rd annual conference of the ieee industrial electronics society, pp 8355–8360. https://doi.org/10.1109/IECON.2017.8217467

  35. Wu J, Chen L, Feng Y, Zheng Z, Zhou MC, Wu Z (2013) Predicting quality of service for selection by neighborhood-based collaborative filtering. IEEE Trans Syst Man Cybern Syst 43(2):428–439. https://doi.org/10.1109/TSMCA.2012.2210409

    Article  Google Scholar 

  36. Yau SS, Gong H, Huang D, Gao W, Zhu L (2008) Specification, decomposition and agent synthesis for situation-aware service-based systems. J Syst Softw 81(10):1663–1680. https://doi.org/10.1016/j.jss.2008.02.035

  37. Yu D, Liu Y, Xu Y, Yin Y (2014) Personalized QoS prediction for web services using latent factor models. In: 2014 IEEE international conference on services computing, pp 107–114. https://doi.org/10.1109/SCC.2014.23

  38. Zhang Y, Zheng Z, Lyu MR (2011) Exploring latent features for memory-based QoS prediction in cloud computing. In: 2011 IEEE 30th international symposium on reliable distributed systems, pp 1–10. https://doi.org/10.1109/SRDS.2011.10

  39. Zheng Z, Ma H, Lyu MR, King I (2011) QoS-aware web service recommendation by collaborative filtering. IEEE Trans Serv Comput 4(2):140–152. https://doi.org/10.1109/TSC.2010.52

    Article  Google Scholar 

  40. Zheng Z, Zhang Y, Lyu MR (2014) Investigating QoS of real-world web services. IEEE Trans Serv Comput 7(1):32–39. https://doi.org/10.1109/TSC.2012.34

    Article  Google Scholar 

Download references

Acknowledgements

This project was financially supported by CAMPUS FRANCE (PHC TOUBKAL 2017 (French-Morocco bilateral program) Grant Number: 36804YH).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Soufiane Faieq.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Faieq, S., Saidi, R., El Ghazi, H. et al. Building adaptive context-aware service-based smart systems. SOCA 15, 21–42 (2021). https://doi.org/10.1007/s11761-020-00310-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11761-020-00310-0

Keywords

Navigation