Context-Aware Service Orchestration in Smart Environments

  • Renato SoicEmail author
  • Marin Vukovic
  • Pavle Skocir
  • Gordan Jezic
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 148)


With rapid technological advancements, smart systems have become an integral part of human environments. Capabilities of such systems are evolving constantly, resulting in broad areas of specific applications, ranging from personal to business and industrial use cases. This has encouraged the development of complex heterogeneous service ecosystems able to perform a wide variety of specific functionalities deployed on diverse physical nodes. Consequently, it has become a greater challenge to both maintain optimal resource utilization and achieve reliable management and orchestration of available services. For this purpose, we propose an agent-based system capable of orchestrating services on system nodes based on current context. This enables simplification of large-scale systems by introducing a generic set of services available to all nodes in the system, while service activation depends on environment state. The proposed solution provides flexibility in versatile environments typically encountered in domains such as smart homes and buildings, smart cities, and Industry 4.0. Additionally, it enables reduced consumption of resources on a given physical node. The described system is evaluated using a case study in the smart building environment, where it is shown how the proposed model can simplify the system and reduce resource utilization.


Software agents Smart environments Industry 4.0 IoT RFID Context-awareness Human–computer interaction Service orchestration 



This work has been supported in part by Croatian Science Foundation under the project 6917 “High-Quality Speech Synthesis for Croatian language” (HR-SYNTH).


  1. 1.
    Wollschlaeger, M., Sauter, T., Jasperneite, J.: The future of industrial communication: Automation networks in the era of the internet of things and industry 4.0. IEEE Ind. Electron. Mag. 11(1), 17–27 (2017)CrossRefGoogle Scholar
  2. 2.
    Wang, S., Wan, J., Zhang, D., Li, D., Zhang, C.: Towards smart factory for industry 4.0: a self-organized multi-agent system with big data based feedback and coordination. Comput. Netw. 101, 158–168 (2016)CrossRefGoogle Scholar
  3. 3.
    Hossain, M.M., Fotouhi, M., Hasan, R.: Towards an analysis of security issues, challenges, and open problems in the internet of things. In: IEEE World Congress on Services, pp. 21–28 (2015)Google Scholar
  4. 4.
    Leitão, P., Mařík, V., Vrba, P.: Past, present, and future of industrial agent applications. IEEE Trans. Ind. Inform. 9(4), 2360–2372 (2013)CrossRefGoogle Scholar
  5. 5.
    Monostori, L.: Cyber-physical production systems: Roots, expectations and R&D challenges. Procedia CIRP 17, 9–13 (2014)CrossRefGoogle Scholar
  6. 6.
    Lu, Y.: Industry 4.0: A survey on technologies, applications and open research issues. J. Ind. Inf. Integr. 6, 1–10 (2017)Google Scholar
  7. 7.
    Leitão, P., Colombo, A.W., Karnouskos, S.: Industrial automation based on cyber-physical systems technologies: Prototype implementations and challenges. Comput. Ind. 81, 11–25 (2016)CrossRefGoogle Scholar
  8. 8.
    Rajkumar, R., Lee, I., Sha, L., Stankovic, J.: Cyber-physical systems: the next computing revolution. In: Design Automation Conference, 47th ACM/IEEE, pp. 731–736 (2010)Google Scholar
  9. 9.
    Cristalli, C., Foehr, M., Jäger, T., Leitao, P., Paone, N., Castellini, P., Turrin, C., Schjolberg, I.: Integration of process and quality control using multi-agent technology. In: 2013 IEEE International Symposium on Industrial Electronics (ISIE), pp. 1–6, (2013)Google Scholar
  10. 10.
    Marín, C.A., Monch, L., Leitao, P., Vrba, P., Kazanskaia, D., Chepegin, V., Liu, L., Mehandjiev, N.: A conceptual architecture based on intelligent services for manufacturing support systems. In: 2013 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 4749–4754 (2013)Google Scholar
  11. 11.
    Soic, R., Skocir, P., Jezic, G.: Agent-based system for context-aware human-computer interaction. In: KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications, pp. 34–43 (2018)Google Scholar
  12. 12.
    Cai, H., Xu, B., Jiang, L., Vasilakos, A.V.: IoT-based big data storage systems in cloud computing: perspectives and challenges. IEEE IoT J. 4(1), 75–87 (2017)Google Scholar
  13. 13.
    López, G., Quesada, L., Guerrero, L.A.: Alexa vs. Siri vs. Cortana vs. Google Assistant: a comparison of speech-based natural user interfaces. In: International Conference on Applied Human Factors and Ergonomics, pp. 241–250 (2017)Google Scholar
  14. 14.
    Gorecky, D., Schmitt, M., Loskyll, M., Zühlke, D.: Human-machine-interaction in the industry 4.0 era. In: 2014 12th IEEE International Conference on Industrial Informatics (INDIN), pp. 289–294 (2014)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Renato Soic
    • 1
    Email author
  • Marin Vukovic
    • 1
  • Pavle Skocir
    • 1
  • Gordan Jezic
    • 1
  1. 1.Faculty of Electrical Engineering and ComputingUniversity of ZagrebZagrebCroatia

Personalised recommendations