Simulated annealing-based reprogramming scheme of wireless sensor nodes

  • Zhangling DuanEmail author
  • Xing Wei
  • Jianghong Han
  • Yang Lu
  • Lei Shi


Code dissemination is a main component of reprogramming which enables over-the-air software update in wireless sensor networks. In this paper, we present a Simulated Annealing-based reprogramming scheme (SA). Unlike well-known wireless reprogramming data dissemination protocols such as Deluge, whose primary goal is to minimize energy consumption, SA’s design criterion is to minimize energy consumption while balancing the energy consumption of the entire sensor network. To achieve these goals, we first establish the NP-hard model of data dissemination routing and its simplified form. Then, the relaying nodes and corresponding communication radius are determined by their remaining energy and the balanced consumption of the covered nodes, respectively. Finally, the iterative optimization strategy with simulated annealing is achieved. Physical experimental results and numerical analysis show that the proposed algorithm can find the near-optimal solutions to reduce and balance the total energy consumption when there is an energy imbalance among different nodes.


Simulated annealing Wireless reprograming Greedy algorithm Set partitioning 



  1. 1.
    Taherkordi, A., Loiret, F., Rouvoy, R., & Eliassen, F. (2013). Optimizing sensor network reprogramming via in situ reconfigurable components. ACM Transactions on Sensor Networks, 9(2), 1–37.CrossRefGoogle Scholar
  2. 2.
    Hagedorn, A., Starobinski, D., & Trachtenberg, A. (2008). Rateless Deluge: Over-the-air programming of wireless sensor networks using random linear codes. In Proceedings of the IEEE international conference on information processing in sensor network (IPSN), pp. 457–466.Google Scholar
  3. 3.
    Jeong, J., Kim, S., & Broad, A. (2003). Network reprogramming, Berkeley, California, USA. Accessed 14 Jan 2013.
  4. 4.
    Stathopoulos, T., Heidemann, J., & Estrin, D. (2009). A remote code update mechanism for wireless sensor networks. In Proceedings of IEEE military communications conference (MILCOM), pp. 1–7.Google Scholar
  5. 5.
    Hui, J. W., & Culler, D. (2004). The dynamic behavior of a data dissemination protocol for network programming at scale. In Proceedings of the 2nd international conference on embedded networked sensor systems (SenSys), pp. 81–94.Google Scholar
  6. 6.
    Kulkarni, S., & Wang, L. (2005). MNP: multihop network reprogramming service for sensor networks. In Proceedings of 25th IEEE international conference on distributed computing systems (ICDCS), pp. 7–16.Google Scholar
  7. 7.
    Naik, V., Arora, A., Sinha, P., & Zhang, H. (2005). Sprinkler: A reliable and energy efficient data dissemination service for wireless embedded devices. In Proceedings of IEEE international real-time systems symposium (RTSS), pp. 1–15.Google Scholar
  8. 8.
    Alam, S. M. I., Sultana, S., Hu, Y. C., & Fahmy, S. (2014). SYREN: Synergistic link correlation-aware and network coding-based dissemination in wireless sensor networks. In Proceedings of 2013 IEEE 21st international symposium on modelling, analysis and simulation of computer and telecommunication systems (MASCOTS), pp. 485–494.Google Scholar
  9. 9.
    Levis, P., & Culler, D. (2002). Mate: A tiny virtual machine for sensor networks. In Proceedings of the 10th international conference on Architectural support for programming languages and operating systems (ASPLOS), pp. 85–95.Google Scholar
  10. 10.
    Panta, R. K., Bagchi, S., & Midkiff, S. P. (2009). Zephyr: Efficient incremental reprogramming of sensor nodes using function call indirections and difference computation. In Proceedings of the 2009 conference on USENIX An-nual technical conference (USENIX), pp. 411–424.Google Scholar
  11. 11.
    Rossi, M., Zanca, G., Stabellini, L., Crepaldi, R., Harris, A. F. I., & Zorzi, M. (2010). SYNAPSE: A network reprogramming protocol for wireless sensor networks using fountain codes. In Proceedings of 5th annual IEEE communications society conference on sensor, mesh and AdHoc communications and networks (SAHCN), pp. 188–196.Google Scholar
  12. 12.
    Reijers, N., & Langendoen, K. (2003). Efficient code distribution in wireless sensor networks. In Proceedings of the 2nd ACM international conference on wireless sensor networks and applications (WSNA), pp. 60–67.Google Scholar
  13. 13.
    Qiu, J., Li, D., Shi, H., & Cui, L. (2014). EasiLIR: Lightweight incremental reprogramming for sensor networks. International Journal of Distributed Sensor Networks, 10(4), 1–15.Google Scholar
  14. 14.
    Huang, L., & Setia, S. (2008). CORD: Energy-efficient reliable bulk data dissemination in sensor networks. In Proceedings of the 27th conference on computer communications (INFCOM), pp. 1247–1255.Google Scholar
  15. 15.
    Kim, D., Nam, H., & Kim, D. (2016). Adaptive code dissemination based on link quality in wireless sensor networks. IEEE Internet of Things Journal, 4(3), 685–694.CrossRefGoogle Scholar
  16. 16.
    Hosseini, S., Khaled, A., & Vadlamani, S. (2014). Hybrid imperialist competitive algorithm, variable neighborhood search, and simulated annealing for dynamic facility layout problem. Neural Computing and Application, 25(7–8), 1871–1885.CrossRefGoogle Scholar
  17. 17.
    Sharma, M., & Sharma, K. (2012). An energy efficient extended LEACH (EEE LEACH). In Proceedings of international conference on communication systems and network technologies (CSNT), pp. 377–382.Google Scholar
  18. 18.
    Kim, S., & Eom, D. S. (2012). Dynamic transmission power control for wireless sensor network reprogramming. In Proceedings of 17th Asia-Pacific conference on communications (APCC), pp. 145–150.Google Scholar
  19. 19.
    Tinyos community forum. Accessed 14 Jan 2013.
  20. 20.
    Dang, H. V., Ngan, L. T. C., Khoa, N. K., & Quan L. T. (2019). Towards an integration of AES cryptography into Deluge dissemination protocol for securing IoTs reconfiguration. In Proceedings of 2019 IEEE-RIVF international conference on computing and communication technologies, pp. 1–6.Google Scholar
  21. 21.
    Do, D. S., & Kim, Y. (2015). Lightweight reprogramming and energy balancing in wireless sensor networks. International Journal of Distributed Sensor Networks, 11(8), 1–8.CrossRefGoogle Scholar
  22. 22.
    Krasniewski, M. D., Panta, R. K., Bagchi, S., Yang, C. L., & Chappell, W. J. (2008). Energy-efficient on-demand reprogramming of large-scale sensor networks. ACM Transactions on Sensor Networks, 4(1), 1–38.CrossRefGoogle Scholar
  23. 23.
    Panta, R. K., Khalil, I., & Bagchi, S. (2007). Stream: Low overhead wireless reprogramming for sensor networks. In Proceedings of 26th IEEE international conference on computer communications (INFCOM), pp. 928–936.Google Scholar
  24. 24.
    Gao, Y., Bu, J., Dong, W., Chen, C., Rao, L., & Liu, X. (2013). Exploiting concurrency for efficient dissemination in wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 24(4), 691–700.CrossRefGoogle Scholar
  25. 25.
    Li, J. W., Li, S. N., Zhang, Y., Gu, T., Law, Y. W., Yang, Z., et al. (2017). An analytical model for coding-based reprogramming protocols in lossy wireless sensor networks. IEEE Transactions on Computers, 66(1), 24–37.MathSciNetzbMATHCrossRefGoogle Scholar
  26. 26.
    Liu, X., Li, G., Zhang, S., & Liu, A. (2018). Big program code dissemination scheme for emergency software-define wireless sensor networks. Peer-to-Peer Networking and Applications, 11(5), 1038–1059.CrossRefGoogle Scholar
  27. 27.
    Mujica, G., & Portilla, J. (2018). Distributed reprogramming on the edge: A new collaborative code dissemination strategy for IoT. Electronics, 8(3), 267–286.CrossRefGoogle Scholar
  28. 28.
    Teng, H., Liu, W., Wang, T., Liu, A., Liu, X., & Zhang, S. (2019). A Cost-efficient greedy code dissemination scheme through vehicle to sensing devices (V2SD) communication in smart city. IEEE ACCESS, 7, 16675–16694.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Zhangling Duan
    • 1
    Email author
  • Xing Wei
    • 1
  • Jianghong Han
    • 1
  • Yang Lu
    • 1
  • Lei Shi
    • 1
  1. 1.School of Computer and InformationHefei University of TechnologyHefeiPeople’s Republic of China

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