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Agent-Based Approach for Energy-Efficient IoT Services Discovery and Management

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Agents and Multi-Agent Systems: Technologies and Applications 2018 (KES-AMSTA-18 2018)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 96))

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Abstract

Internet of Things (IoT) systems are becoming omnipresent, with miscellaneous solutions in diverse domains. To release the full potential of the IoT, it is needed to have dynamic user-centric systems where services can be executed according to user demands. A growing number of devices that is being deployed need to be capable to be discovered easily by the IoT platforms, and offer their services automatically, without human intervention. Due to the complexity of IoT systems, automatic discovery and management of services offered by IoT devices is rarely aligned with user demands. In this paper we propose an agent-based approach which enables the discovery and management of IoT services. Furthermore, it enables the control of devices according to user-defined rules or direct commands.

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References

  1. Carballido Villaverde, B., Alberola, R.D.P., Jara, A.J., Fedor, S., Das, S.K., Pesch, D.: Service discovery protocols for constrained machine-to-machine communications. IEEE Commun. Surv. Tutor. 16(1), 41–60 (2014)

    Article  Google Scholar 

  2. Cirani, S., Davoli, L., Ferrari, G., Leone, R., Medagliani, P., Picone, M., Veltri, L.: A scalable and self-configuring architecture for service discovery in the Internet of Things. IEEE Internet Things J. 1(5), 508–521 (2014)

    Article  Google Scholar 

  3. Datta, S.K., Da Costa, R.P.F., Bonnet, C.: Resource discovery in Internet of Things: current trends and future standardization aspects. In: Proceedings of the IEEE World Forum on Internet of Things, WF-IoT 2015, pp. 542–547 (2015)

    Google Scholar 

  4. Georgakopoulos, D., Jayaraman, P.P., Zhang, M., Ranjan, R.: Discovery-driven service oriented IoT architecture. In: Proceedings of the IEEE Conference on Collaboration and Internet Computing, CIC 2015, pp. 142–149 (2016)

    Google Scholar 

  5. Gubbi, J., Buyya, R., Marusic, S., Palaniswami, M.: Internet of Things (IoT): a vision, architectural elements, and future directions. Fut. Gener. Comput. Syst. 29(7), 1645–1660 (2013)

    Article  Google Scholar 

  6. Helal, R., ElMougy, A.: An energy-efficient service discovery protocol for the IoT based on a multi-tier WSN architecture. In: Proceedings of Conference on Local Computer Networks, LCN 2015, pp. 862–869, December 2015

    Google Scholar 

  7. Jara, A.J., Lopez, P., Fernandez, D., Castillo, J.F., Zamora, M.A., Skarmeta, A.F.: Mobile digcovery: a global service discovery for the Internet of Things. In: Proceedings of the 27th International Conference on Advanced Information Networking and Applications Workshops, WAINA 2013, pp. 1325–1330 (2013)

    Google Scholar 

  8. oneM2M: M2M Functional Architecture. Technical Specification (2016). http://www.onem2m.org/images/files/deliverables/Release2/TS-0001-%20Functional_Architecture-V2_10_0.pdf

  9. Open Mobile Alliance (OMA): OMA Device Management Protocol. Technical Specification (2016). http://www.openmobilealliance.org/release/DM/V1_3-20160524-A/OMA-TS-DM_Protocol-V1_3-20160524-A.pdf

  10. Palattella, M.R., Dohler, M., Grieco, A., Rizzo, G., Torsner, J., Engel, T., Ladid, L.: Internet of Things in the 5G era: enablers, architecture, and business models. IEEE J. Sel. Areas Commun. 34(3), 510–527 (2016)

    Article  Google Scholar 

  11. Skocir, P., Kusek, M., Jezic, G.: Energy-efficient task allocation for service provisioning in machine-to-machine systems. Concurr. Comput. Pract. Exp. 29(23), 1–22 (2017)

    Article  Google Scholar 

  12. Statista: Internet of Things (IoT) connected devices installed base worldwide from 2015 to 2025 (in billions) (2018). https://www.statista.com/statistics/471264/iot-number-of-connected-devices-worldwide/

  13. Vinyals, M., Rodriguez-Aguilar, J.A., Cerquides, J.: A survey on sensor networks from a multiagent perspective. Comput. J. 54(3), 455–470 (2011)

    Article  Google Scholar 

  14. Wang, E., Chow, R.: What can i do here? IoT service discovery in smart cities. In: IEEE International Conference on Pervasive Computing and Communication Workshops, PerCom Workshops 2016 (2016)

    Google Scholar 

Download references

Acknowledgements

This work is supported by the H2020 symbIoTe project, which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 688156.

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Authors and Affiliations

  1. Faculty of Electrical Engineering and Computing, Internet of Things Laboratory, University of Zagreb, Unska 3, 10000, Zagreb, Croatia

    Petar Krivic, Pavle Skocir & Mario Kusek

Authors
  1. Petar Krivic
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  2. Pavle Skocir
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  3. Mario Kusek
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Corresponding author

Correspondence to Pavle Skocir .

Editor information

Editors and Affiliations

  1. University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, Croatia

    Gordan Jezic

  2. The Heriot-Watt University, Edinburgh, United Kingdom

    Yun-Heh Jessica Chen-Burger

  3. Bournemouth University, Poole, United Kingdom

    Robert J. Howlett

  4. Centre for Artificial Intelligence, Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, New South Wales, Australia

    Lakhmi C. Jain

  5. Griffith Sciences - Centres and Institutes, Griffith University, South Brisbane, Queensland, Australia

    Ljubo Vlacic

  6. Department of Business Economics and Management and Silesian University in Opava, School of Business Administration in Karvina, Karvina, Czech Republic

    Roman Šperka

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Krivic, P., Skocir, P., Kusek, M. (2019). Agent-Based Approach for Energy-Efficient IoT Services Discovery and Management. In: Jezic, G., Chen-Burger, YH., Howlett, R., Jain, L., Vlacic, L., Šperka, R. (eds) Agents and Multi-Agent Systems: Technologies and Applications 2018. KES-AMSTA-18 2018. Smart Innovation, Systems and Technologies, vol 96. Springer, Cham. https://doi.org/10.1007/978-3-319-92031-3_6

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