Logo PTI Logo FedCSIS

Proceedings of the 17th Conference on Computer Science and Intelligence Systems

Annals of Computer Science and Information Systems, Volume 30

Self-adaptive Device Management for the IoT Using Constraint Solving

, , ,

DOI: http://dx.doi.org/10.15439/2022F80

Citation: Proceedings of the 17th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 30, pages 641–650 ()

Full text

Abstract. In the context of IoT, Device Management (DM), i.e., remote administration of IoT devices, becomes essential to keep them connected, updated and secure, thus increasing their lifespan through firmware and configuration updates and security patches. Legacy DM solutions are adequate when dealing with home devices (such as TV set-top boxes) but need to be extended to adapt to new IoT requirements. Indeed, their manual operation by system administrators requires advanced knowledge and skills. Further, the static DM platform --- a component above IoT platforms that offers advanced features such as campaign updates / massive operation management --- is unable to scale and adapt to IoT dynamicity. To cope with this, this work, performed in an industrial context at Orange, proposes a self-adaptive architecture with runtime horizontal scaling of DM servers, with an autonomic Auto-Scaling Manager, integrating in the loop constraint programming for decision-making, validated with a meaningful industrial use-case.

References

  1. F. Aïssaoui, S. Berlemont, M. Douet, and E. Mezghani, “A semantic model toward smart iot device management,” in Workshops of the International Conf on Advanced Information Networking and Applications, (Caserta, Italy), pp. 640–650, Springer Publishing, 2020.
  2. T. Perumal, S. K. Datta, and C. Bonnet, “Iot device management framework for smart home scenarios,” in 2015 IEEE 4th Global Conf on Consumer Electronics (GCCE), (Japan), pp. 54–55, IEEE, 2015.
  3. K. Shea, “Device management in the internet of things–why it matters and how to achieve it.” http://www.new-techeurope.com/2017/06/07/device-management-internet-things-matters-achieve/, 2017. Accessed on 2021-02-20.
  4. A. Computing et al., “An architectural blueprint for autonomic computing,” IBM White Paper, vol. 31, no. 2006, pp. 1–6, 2006.
  5. F. Rossi, P. Van Beek, and T. Walsh, Handbook of constraint programming. USA: Elsevier, 2006.
  6. B. Forum, “Tr-069 cpe wan management protocol.” https://www.broadband-forum.org/download/TR-069_Amendment-6.pdf, 2018. Accessed on 2021-02-23.
  7. O. M. Alliance, “Lightweight machine to machine technical specification,” Approved Version, vol. 1, no. 1, 2017.
  8. M. Elkhodr, S. Shahrestani, and H. Cheung, “The internet of things: new interoperability, management and security challenges,” arXiv preprint https://arxiv.org/abs/1604.04824, vol. abs/1604.04824, p. 85–102, 2016.
  9. J. Lin, W. Yu, N. Zhang, X. Yang, H. Zhang, and W. Zhao, “A survey on internet of things: Architecture, enabling technologies, security and privacy, and applications,” IEEE Internet of Things Journal, 2017.
  10. Z. Wen, R. Yang, P. Garraghan, T. Lin, J. Xu, and M. Rovatsos, “Fog orchestration for internet of things services,” IEEE Internet Computing, vol. 21, no. 2, pp. 16–24, 2017.
  11. J. H. Ziegeldorf, O. G. Morchon, and K. Wehrle, “Privacy in the internet of things: threats and challenges,” Security and Communication Networks, vol. 7, no. 12, pp. 2728–2742, 2014.
  12. N. Ayeb, E. Rutten, S. Bolle, T. Coupaye, and M. Douet, “Towards an autonomic and distributed device management for the internet of things,” in IEEE 4th International Workshops on Foundations and Applications of Self* Systems, (Sweden), pp. 246–248, IEEE, 2019.
  13. N. Ayeb, E. Rutten, S. Bolle, T. Coupaye, and M. Douet, “Coordinated autonomic loops for target identification, load and error-aware device management for the iot,” in 15th Conference on Computer Science and Information Systems (FedCSIS), (Bulgaria), pp. 491–500, IEEE, 2020.
  14. J. O. Kephart and D. M. Chess, “The vision of autonomic computing,” Computer, vol. 36, no. 1, pp. 41–50, 2003.
  15. M. Tahir, Q. M. Ashraf, and M. Dabbagh, “Towards enabling autonomic computing in iot ecosystem,” in IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress, (Japan), IEEE, 2019.
  16. F. A. Salaht, F. Desprez, and A. Lebre, “An overview of service placement problem in fog and edge computing,” ACM Surveys, 2020.
  17. B. Donassolo, IoT Orchestration in the Fog.(L’orchestration des applications IoT dans le Fog). PhD thesis, Grenoble Alpes University, France, 2020.
  18. S. Challita, F. Paraiso, and P. Merle, “A study of virtual machine placement optimization in data centers,” in 7th International Conference on Cloud Computing and Services Science, (Porto, Portugal), pp. 343–350, INSTICC, 2017.
  19. B. Donassolo, I. Fajjari, A. Legrand, and P. Mertikopoulos, “Load aware provisioning of iot services on fog computing platform,” in ICC IEEE International Conf on Communications, (China), pp. 1–7, IEEE, 2019.
  20. F. A. Salaht, F. Desprez, A. Lebre, C. Prud’Homme, and M. Abderrahim, “Service placement in fog computing using constraint programming,” in IEEE International Conf on Services Computing, (Italy), IEEE, 2019.
  21. Y. Xia, Combining Heuristics for Optimizing and Scaling the Placement of IoT Applications in the Fog. PhD thesis, Université Grenoble Alpes, 2018.
  22. C. Prud’homme, J.-G. Fages, and X. Lorca, “Choco solver documentation,” TASC, INRIA Rennes, LINA CNRS UMR, vol. 6241, 2016.
  23. L. Perron and V. Furnon, “Google’s or-tools,” 2019.
  24. P. Laborie, J. Rogerie, P. Shaw, and P. Vilím, “Ibm ilog cp optimizer for scheduling,” Constraints, vol. 23, no. 2, pp. 210–250, 2018.
  25. S. R. Department, “Internet of things- active connections worldwide 2015-2025.” https://www.statista.com/statistics/1101442/iot-number-of-connected-devices-worldwide/, Jan 2021. Accessed on 2021-02-23.
  26. K. Fizza, N. Auluck, A. Azim, M. A. Maruf, and A. Singh, “Faster ota updates in smart vehicles using fog computing,” in Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing Companion, (New York, NY, USA), pp. 59–64, Association for Computing Machinery, 2019.
  27. P. Shaw, “A constraint for bin packing,” in International conference on principles and practice of constraint programming, (Berlin), pp. 648–662, Springer, 2004.
  28. J.-C. Régin, “A filtering algorithm for constraints of difference in csps,” in AAAI, (USA), pp. 362–367, American Association for AI, 1994.
  29. G. Pesant, “A regular language membership constraint for finite sequences of variables,” in International Conf on principles and practice of constraint programming, (Heidelberg), pp. 482–495, Springer, 2004.
  30. F. Pezoa, J. L. Reutter, F. Suarez, M. Ugarte, and D. Vrgoč, “Foundations of json schema,” in Proceedings of the 25th International Conference on World Wide Web, (Republic and Canton of Geneva, CHE), pp. 263–273, International World Wide Web Conferences Steering Committee, 2016.
  31. A. RabbitMQ, “Messaging that just works - rabbitmq,” 2020. Accessed 07-June-2021.
  32. M. Mao and M. Humphrey, “A performance study on the vm startup time in the cloud,” in 2012 IEEE Fifth International Conference on Cloud Computing, (Honolulu, HI, USA), pp. 423–430, IEEE, 2012.
  33. M. Litoiu, M. Shaw, G. Tamura, N. M. Villegas, H. Müller, H. Giese, R. Rouvoy, and E. Rutten, “What Can Control Theory Teach Us About Assurances in Self-Adaptive Software Systems?,” in Software Engineering for Self-Adaptive Systems 3: Assurances, vol. 9640, Springer, May 2017.
  34. D. Balouek, A. C. Amarie, G. Charrier, F. Desprez, E. Jeannot, E. Jeanvoine, A. Lèbre, D. Margery, N. Niclausse, and L. Nussbaum, “Adding virtualization capabilities to the grid’5000 testbed,” in International Conf on Cloud Computing and Services Science, pp. 3–20, Springer, 2012.
  35. C. Adjih, E. Baccelli, E. Fleury, G. Harter, N. Mitton, T. Noel, R. Pissard-Gibollet, F. Saint-Marcel, G. Schreiner, J. Vandaele, and T. Watteyne, “Fit iot-lab: A large scale open experimental iot testbed,” in IEEE 2nd World Forum on IoT, (Italy), pp. 459–464, IEEE, 2015.