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Non-intrusive contextual dynamic reconfiguration of ambient intelligent IoT systems

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Abstract

Internet of Things is the current evolution of the Internet, which is opening tremendous opportunities for a large number of novel applications that promise to revolutionize and improve the quality of human life. For this reason, much attention has been oriented towards this theme from different perspectives. The problem treated by this paper is the necessity of having a mechanism that enables IoT systems to perform with transparency without stops or breaks regardless of the changes that affect the surrounding context. We propose a contextual dynamic reconfiguration process to be applied on the architectural level of IoT systems; the process relies on autonomic computing MAPE-K loop. The originality of our work is the use of architectural styles to make reusable all the architectural evolutions applied on the system.

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References

  • Acosta Padilla FJ, Weis F et al (2014) Towards a model@ runtime middleware for cyber physical systems. In: Proceedings of the 9th workshop on middleware for next generation internet computing, ACM

  • Al-Fuqaha A, Guizani M et al (2015) Internet of things: a survey on enabling technologies, protocols, and applications. IEEE Commun Surv Tutor 17(4):2347–2376

    Article  Google Scholar 

  • Ashton K (2009) That ‘internet of things’ thing. RFID J 22(7):97–114

    Google Scholar 

  • Atzori L, Iera A et al (2010) The internet of things: a survey. Comput Netw 54(15):2787–2805

    Article  Google Scholar 

  • Azimi I, Rahmani AM et al (2017) Internet of things for remote elderly monitoring: a study from user-centered perspective. J Ambient Intell Humaniz Comput 8(2):273–289

    Article  Google Scholar 

  • Benghozi P-J, Bureau S et al (2012) Internet of things: what challenges for Europe. Les Editions de la MSH, Paris

    Google Scholar 

  • Bettini C, Brdiczka O et al (2010) A survey of context modelling and reasoning techniques. Pervasive Mob Comput 6(2):161–180

    Article  Google Scholar 

  • Blomstedt J (2008) A unified approach to adaptive code selection for modern systems. University of Colorado, Boulder

    Google Scholar 

  • Brogi A, Cámara J et al (2007) Dynamic contextual adaptation. Electron Notes Theor Comput Sci 175(2):81–95

    Article  Google Scholar 

  • Coen MH (1998) Design principles for intelligent environments. AAAI/IAAI

  • Conan D, Rouvoy R et al (2007) Scalable processing of context information with COSMOS. In: IFIP international conference on distributed applications and interoperable systems, Springer

  • Corradi A, Lodolo E et al (2009) Dynamic reconfiguration of middleware for ubiquitous computing. In: Proceedings of the 3rd international workshop on Adaptive and dependable mobile ubiquitous systems, ACM

  • Da Xu L, He W et al (2014) Internet of things in industries: a survey. IEEE Trans Ind Inform 10(4):2233–2243

    Article  Google Scholar 

  • Darwish A, Hassanien AE (2018) Cyber physical systems design, methodology, and integration: the current status and future outlook. J Ambient Intell Humaniz Comput 9(5):1541–1556

    Article  Google Scholar 

  • Ferry N, Lavirotte S et al (2008) Adaptation Dynamique d’Applications au Contexte en Informatique Ambiante. Rapport Technique, Laboratoire I3S (Universite de Nice Sophia Antipolis/CNRS), numero I3S/RR-2008-20-FR, Sophia Antipolis, France

  • Floch J, Hallsteinsen S et al (2006) Using architecture models for runtime adaptability. IEEE Softw 23(2):62–70

    Article  Google Scholar 

  • Garlan D, Siewiorek DP et al (2002) Project aura: Toward distraction-free pervasive computing. IEEE Pervasive Comput 1(2):22–31

    Article  Google Scholar 

  • Guthikonda RT, Chitta SS et al (2014) Comparative analysis of IoT architectures. TLEN 5710 Capstone, Tech. Rep

  • Hassan A, Queudet A et al (2016) Evolution style: framework for dynamic evolution of real-time software architecture. In: European conference on software architecture, Springer

  • Kaasinen E (2003) User needs for location-aware mobile services. Pers Ubiquitous Comput 7(1):70–79

    Article  Google Scholar 

  • Khan R, Khan SU et al (2012) Future internet: the internet of things architecture, possible applications and key challenges. In: Frontiers of information technology (FIT), 2012 10th international conference on, IEEE

  • Kirsch Pinheiro M (2006) Adaptation contextuelle et personnalisée de l’information de conscience de groupe au sein des Systèmes d’Information coopératifs. Université Joseph Fourier, Grenoble

    Google Scholar 

  • Kortuem G, Kawsar F et al (2010) Smart objects as building blocks for the internet of things. IEEE Internet Comput 14(1):44–51

    Article  Google Scholar 

  • Le Goaer O (2009) Styles d’évolution dans les architectures logicielles, Université de Nantes; Ecole Centrale de Nantes (ECN)(ECN)(ECN)(ECN)

  • Le Goaer O, Oussalah M et al (2007) Evolution dirigée par les styles. Atelier RIMEL (Rétro-Ingénierie, Maintenance et Evolution des Logiciels)

  • Marconi A, Pistore M et al (2009) Enabling adaptation of pervasive flows: built-in contextual adaptation. Service-Oriented Computing. Springer, New York, pp 445–454

    Google Scholar 

  • Musumba GW, Nyongesa HO (2013) Context awareness in mobile computing: a review. Int J Mach Learn Appl 2(1):5

    Google Scholar 

  • Preuveneers D, Van den Bergh J et al (2004) Towards an extensible context ontology for ambient intelligence. In: European symposium on ambient intelligence, Springer

  • Rao L, Fan C et al (2015) A self-adapting dynamic service management platform for internet of things. LISS 2013. Springer, New York, pp 783–791

    Google Scholar 

  • Scholze S, Barata J (2016) Context awareness for flexible manufacturing systems using cyber physical approaches. In: Doctoral conference on computing, electrical and industrial systems, Springer

  • Su J-M, Tseng S-S et al (2011) A personalized learning content adaptation mechanism to meet diverse user needs in mobile learning environments. User Model User Adapt Interact 21(1):5–49

    Article  Google Scholar 

  • Talbot V, Benyahia I (2010) Complex application architecture dynamic reconfiguration based on multi-criteria decision making. Int J Software Engineer Appl 1(4):19–37

    Google Scholar 

  • Whitmore A, Agarwal A et al (2015) The Internet of Things—a survey of topics and trends. Inf Syst Front 17(2):261–274

    Article  Google Scholar 

  • Wojciechowski M, Xiong J (2008) On context modeling in ambient assisted living. In: Fifth international workshop modeling and reasoning in context (MRC 08), Delft, Niederlande

  • Wu M, Lu T-J et al (2010) Research on the architecture of Internet of things. In: Advanced computer theory and engineering (ICACTE), 2010 3rd international conference on, IEEE

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Authors and Affiliations

  1. LISCO Laboratory, University of Badji Mokhtar, Annaba, 23000, Algeria

    Amira Hakim

  2. LIM Laboratory, University of Souk Ahras, Souk Ahras, 41000, Algeria

    Abdelkrim Amirat

  3. LINA Laboratory, University of Nantes, Nantes, 44322, France

    Mourad Chabane Oussalah

Authors
  1. Amira Hakim
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  2. Abdelkrim Amirat
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  3. Mourad Chabane Oussalah
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Correspondence to Amira Hakim.

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Hakim, A., Amirat, A. & Oussalah, M.C. Non-intrusive contextual dynamic reconfiguration of ambient intelligent IoT systems. J Ambient Intell Human Comput 11, 1365–1376 (2020). https://doi.org/10.1007/s12652-018-1127-2

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  • DOI: https://doi.org/10.1007/s12652-018-1127-2

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