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Position and Communication Papers of the 16th Conference on Computer Science and Intelligence Systems

Annals of Computer Science and Information Systems, Volume 26

Connectivity Maintenance in IoT-based Mobile Networks: Approaches and Challenges


DOI: http://dx.doi.org/10.15439/2021F102

Citation: Position and Communication Papers of the 16th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 26, pages 145149 ()

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Abstract. Losing some nodes in multi-hop networks may cutoff all communication paths between other active nodes. Generally the connectivity of a partitioned network can be restored by adding new or activating redundant nodes, moving available nodes to new location and increasing the wireless communication range of nodes. The restoration problem may have many constraint and sub problems. The network may initially disconnected, the nodes may be heterogeneous, reliable connections maybe required between the nodes and more than one node may fail at same time. In this paper, we study the main challenges of connectivity restoration in IoT based wireless networks.


  1. S. Arslan, M. Challenger, and O. Dagdeviren, “Wireless Sensor Network based Fire Detection System for Libraries,” in 2017 International Conference on Computer Science and Engineering (UBMK). IEEE, 2017, pp. 271–276.
  2. L. Özgür, V. K. Akram, M. Challenger, and O. Dağdeviren, “An IoT based Smart Thermostat,” in 2018 5th International Conference on Electrical and Electronic Engineering (ICEEE). IEEE, 2018, pp. 252–256.
  3. B. Karaduman, T. Aşıcı, M. Challenger, and R. Eslampanah, “A cloud and Contiki based Fire Detection System using Multi-hop Wireless Sensor Networks,” in Proceedings of the Fourth International Conference on Engineering & MIS 2018, 2018, pp. 1–5.
  4. B. Karaduman, M. Challenger, and R. Eslampanah, “ContikiOS based Library Fire Detection System,” in 2018 5th International Conference on Electrical and Electronic Engineering (ICEEE). IEEE, 2018, pp. 247–251.
  5. N. Karimpour, B. Karaduman, A. Ural, M. Challenger, and O. Dagdeviren, “IoT based Hand Hygiene Compliance Monitoring,” in 2019 International Symposium on Networks, Computers and Communications (ISNCC). IEEE, 2019, pp. 1–6.
  6. M. S. Mekala and P. Viswanathan, “A survey: Smart agriculture iot with cloud computing,” in 2017 international conference on microelectronic devices, circuits and systems (ICMDCS). IEEE, 2017, pp. 1–7.
  7. S. Shao, A. Khreishah, and I. Khalil, “Enabling real-time indoor tracking of iot devices through visible light retroreflection,” IEEE Transactions on Mobile Computing, vol. 19, no. 4, pp. 836–851, 2019.
  8. Y. Jie, J. Y. Pei, L. Jun, G. Yun, and X. Wei, “Smart home system based on iot technologies,” in 2013 International conference on computational and information sciences. IEEE, 2013, pp. 1789–1791.
  9. I. E. Etim and J. Lota, “Power control in cognitive radios, internet-of things (iot) for factories and industrial automation,” in IECON 2016-42nd Annual Conference of the IEEE Industrial Electronics Society. IEEE, 2016, pp. 4701–4705.
  10. T. Ahn, J. Seok, I. Lee, and J. Han, “Reliable flying iot networks for uav disaster rescue operations,” Mobile Information Systems, vol. 2018, 2018.
  11. S. L. Ullo and G. Sinha, “Advances in smart environment monitoring systems using iot and sensors,” Sensors, vol. 20, no. 11, p. 3113, 2020.
  12. N. H. Motlagh, M. Bagaa, and T. Taleb, “Uav-based iot platform: A crowd surveillance use case,” IEEE Communications Magazine, vol. 55, no. 2, pp. 128–134, 2017.
  13. M. Hassanalian and A. Abdelkefi, “Classifications, applications, and design challenges of drones: A review,” Progress in Aerospace Sciences, vol. 91, pp. 99–131, 2017.
  14. V. K. Akram and O. Dagdeviren, “Deck: A distributed, asynchronous and exact k-connectivity detection algorithm for wireless sensor networks,” Computer Communications, vol. 116, pp. 9–20, 2018.
  15. Y. Zhang, J. Wang, and G. Hao, “An autonomous connectivity restoration algorithm based on finite state machine for wireless sensor-actor networks,” Sensors, vol. 18, no. 1, p. 153, 2018.
  16. V. K. Akram and O. DAĞDEVİREN, “Tapu: Test and pick up-based k-connectivity restoration algorithm for wireless sensor networks,” Turkish Journal of Electrical Engineering & Computer Sciences, vol. 27, no. 2, pp. 985–997, 2019.
  17. Y. Zeng, L. Xu, and Z. Chen, “Fault-tolerant algorithms for connectivity restoration in wireless sensor networks,” Sensors, vol. 16, no. 1, p. 3, 2016.
  18. M. Imran, M. Younis, A. M. Said, and H. Hasbullah, “Localized motion-based connectivity restoration algorithms for wireless sensor and actor networks,” Journal of Network and Computer Applications, vol. 35, no. 2, pp. 844–856, 2012.
  19. N. Tamboli and M. Younis, “Coverage-aware connectivity restoration in mobile sensor networks,” Journal of network and computer applications, vol. 33, no. 4, pp. 363–374, 2010.
  20. H. M. Marah, R. Eslampanah, and M. Challenger, “DSML4TinyOS: Code Generation for Wireless Devices,” in 2nd International Workshop on Model-Driven Engineering for the Internet-of-Things (MDE4IoT), 21st International Conference on Model Driven Engineering Languages and Systems (MODELS2018). Copenhagen, Denmark, 2018.
  21. T. Z. Asici, B. Karaduman, R. Eslampanah, M. Challenger, J. Denil, and H. Vangheluwe, “Applying Model Driven Engineering Techniques to the Development of Contiki-based IoT Systems,” in 2019 IEEE/ACM 1st International Workshop on Software Engineering Research & Practices for the Internet of Things (SERP4IoT). IEEE, 2019, pp. 25–32.