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ConQeng: A Middleware for Quality of Context Aware Selection, Measurement and Validation

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Internet of Things (GIoTS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13533))

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Abstract

A set of quality metrics (e.g., timeliness, completeness) together represent the Quality of Context (QoC); their values determine the usability of context to context consumers (IoT applications). Therefore, obtaining adequate ‘QoC from the context providers (context sources) represents a significant research challenge. This paper presents a framework called conQeng that addresses such a challenge through novel approaches in QoC-aware selection, QoC measurement and validation. ConQeng selects the potential context providers that deliver an adequate QoC during runtime, assesses their performance - for further selection, and transfers QoC-assured context to the context management platforms (CMPs). We have implemented conQeng in a simulated scenario involving autonomous cars, marketing service agencies as context consumers, and thermal and video cameras as context providers. The results demonstrate that it outperforms three heuristic approaches in reducing context acquisition cost and improving effectiveness and performance efficiency while obtaining adequate QoC.

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References

  1. Dey, A.: Understanding and using context. Pers. Ubiquit. Comput. 5, 4–7 (2001) https://doi.org/10.1007/s007790170019

  2. Perera, C., Zaslavsky, A., Christen, P., Georgakopoulos, D.: CA4IOT: context awareness for Internet of Things. In: 2012 IEEE International Conference on Green Computing and Communications, pp. 775–782. IEEE (2012)

    Google Scholar 

  3. Hassani, A., Medvedev, A., Zaslavsky, A., Delir Haghighi, P., Jayaraman, P., Ling, S.: Efficient execution of complex context queries to enable near real-time smart IoT applications. Sensors. 19, 5457 (2019)

    Article  Google Scholar 

  4. Buchholz, T., Küpper, A., Schiffers, M.: Quality of Context: what it is and why we need it. In: 2003 Workshop of the HP Open View University Association, pp. 1–14. (2003)

    Google Scholar 

  5. Manzoor, A., Truong, H., Dustdar, S.: Quality of Context: models and applications for context-aware systems in pervasive environments. Knowl Eng. Rev. 29, 154–170 (2014)

    Article  Google Scholar 

  6. Brgulja, N., Kusber, R., David, K., Baumgarten, M.: Measuring the probability of correctness of contextual information in context aware systems. In: 2009 IEEE International Symposium on Dependable, Autonomic and Secure Computing, pp. 246–253. IEEE (2009)

    Google Scholar 

  7. https://www.didiglobal.com/science/intelligent-driving. Accessed May 2022

  8. https://www.pedestrian.melbourne.vic.gov.au/. Accessed May 2022

  9. Ma, H., Zeng, C., Ling, C.X.: A reliable people counting system via multiple cameras. ACM Trans. Intell. Syst. Technol. 3, 1–22 (2012)

    Article  Google Scholar 

  10. Kristoffersen, M.S., Dueholm, J. V., Gade, R., Moeslund, T.B.: Pedestrian counting with occlusion handling using stereo thermal cameras. Sensors (Switzerland). 16, 62 (2016)

    Google Scholar 

  11. Li, X., Eckert, M., Martinez, J.F., Rubio, G.: Context aware middleware architectures: survey and challenges. Sensors (Switzerland) 15, 20570–20607 (2015)

    Article  Google Scholar 

  12. Javaid, S., Afzal, H., Arif, F., Iltaf, N., Abbas, H., Iqbal, W.: CATSWoTS: context aware trustworthy social web of things system. Sensors (Switzerland) 19, (2019)

    Google Scholar 

  13. Kowshalya, A.M., Valarmathi, M.L.: Trust management in the social internet of things. Wirel. Pers. Commun. 96, 2681–2691 (2017)

    Article  Google Scholar 

  14. Sicari, S., Rizzardi, A., Miorandi, D., Cappiello, C., Coen-Porisini, A.: A secure and quality-aware prototypical architecture for the Internet of Things. Inf. Syst. 58, 43–55 (2016)

    Article  Google Scholar 

  15. Marie, P., Lim, L., Manzoor, A., Chabridon, S., Conan, D., Desprats, T.: QoC-aware context data distribution in the internet of things. In: 2014 Proceedings of the 1st ACM Workshop on Middleware for Context-Aware Applications in the IoT, pp. 13–18. (2014)

    Google Scholar 

  16. Filho, J., Miron, A., Satoh, I., Gensel, J., Martin, H.: Modeling and measuring quality of context information in pervasive environments. In: 2010 24th IEEE International Conference on Advanced Information Networking and Applications, pp. 690–697. IEEE (2010)

    Google Scholar 

  17. Marie, Pierrick, Desprats, Thierry, Chabridon, Sophie, Sibilla, Michelle: QoCIM: A Meta-model for Quality of Context. In: Brézillon, Patrick, Blackburn, Patrick, Dapoigny, Richard (eds.) CONTEXT 2013. LNCS (LNAI), vol. 8175, pp. 302–315. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-40972-1_23

    Chapter  Google Scholar 

  18. Jagarlamudi, K.S., Zaslavsky, A., Loke, S.W., Hassani, A., Medvedev, A.: Quality and cost aware service selection in IoT-context management platforms. In: 2021 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics), pp. 89–98. IEEE (2021)

    Google Scholar 

  19. Hossain, M.A., Atrey, P.K., El Saddik, A.: Learning multi-sensor confidence using difference of opinions. In: 2008 IEEE Instrumentation and Measurement Technology Conference, pp. 809–813. IEEE, (2008)

    Google Scholar 

  20. Yasar, A.U.H., Paridel, K., Preuveneers, D., Berbers, Y.: When efficiency matters: towards quality of context-aware peers for adaptive communication in VANETs. In: 2011 IEEE Intelligent Vehicles Symposium (IV), pp. 1006–1012. IEEE, (2011)

    Google Scholar 

  21. https://github.com/IBA-Group-IT/IoT-data-simulator . Accessed May (2022)

  22. Hassani, A., et al.: Context-as-a-Service Platform: exchange and share context in an IoT ecosystem. In: 2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), pp. 385–390. IEEE, (2018)

    Google Scholar 

  23. FIWARE - Open APIs for Open Minds. https://www.fiware.org/. Accessed 27 (2022)

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Authors and Affiliations

  1. School of Information Technology, Deakin University, Geelong, Australia

    Kanaka Sai Jagarlamudi, Arkady Zaslavsky, Seng W. Loke, Alireza Hassani & Alexey Medvedev

Authors
  1. Kanaka Sai Jagarlamudi
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  2. Arkady Zaslavsky
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  3. Seng W. Loke
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  4. Alireza Hassani
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  5. Alexey Medvedev
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Corresponding author

Correspondence to Kanaka Sai Jagarlamudi .

Editor information

Editors and Affiliations

  1. University of Murcia, Murcia, Spain

    Aurora González-Vidal

  2. Central Michigan University, Mount Pleasant, MI, USA

    Ahmed Mohamed Abdelgawad

  3. University of Quebec at Montreal, Montreal, QC, Canada

    Essaid Sabir

  4. IoT Forum, Mandat International, Geneva, Switzerland

    Sébastien Ziegler

  5. University of Luxembourg, Esch-sur-Alzette, Luxembourg

    Latif Ladid

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Sai Jagarlamudi, K., Zaslavsky, A., Loke, S.W., Hassani, A., Medvedev, A. (2022). ConQeng: A Middleware for Quality of Context Aware Selection, Measurement and Validation. In: González-Vidal, A., Mohamed Abdelgawad, A., Sabir, E., Ziegler, S., Ladid, L. (eds) Internet of Things. GIoTS 2022. Lecture Notes in Computer Science, vol 13533. Springer, Cham. https://doi.org/10.1007/978-3-031-20936-9_17

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  • DOI: https://doi.org/10.1007/978-3-031-20936-9_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-20935-2

  • Online ISBN: 978-3-031-20936-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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