Parent-Aware Routing for IoT Networks

  • Necip GozuacikEmail author
  • Sema Oktug
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9247)


The deployment of wireless sensor networks (WSNs) accessible through the Internet has caused a growing trend for IoT (Internet of Things). RPL (IPv6 Routing Protocol for Low-Power and Lossy Networks) is proposed by IETF (Internet Engineering Task Force) for IPv6 (Internet Protocol Version 6) constrained IoT networks as the routing protocol. Here, Objective Function (OF) determines how RPL nodes translate metrics into ranks and select routes in a network. This paper introduces a solution to have a load balanced network based on Parent-Aware Objective Function (PAOF). PAOF uses both ETX (Expected Transmission Count) and parent count metrics to compute the best path for routing. This paper evaluates the proposed solution by implementing in Contiki OS (Operating System) with Cooja simulation. MRHOF (Minimum Rank with Hysteresis Objective Function) is used for comparison. Simulation results verify that PAOF gives better parent load density, delay and parent diversity.


IoT Wireless sensor network RPL Objective function Load balancing 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Akyildiz, I.F., Melodia, T., Chowdury, K.R.: Wireless multimedia sensor networks: A survey. IEEE Wireless Communications 14(6), 32–39 (2007)CrossRefGoogle Scholar
  2. 2.
    Milinkovic, A., Milinkovic, S., Lazic, L.: Some experiences in building IoT platform. In: 22nd Telecommunications Forum Telfor, pp. 1138–1141 (2014)Google Scholar
  3. 3.
    Chen, S., Xu, H., Liu, D., Hu, B.: A Vision of IoT: Applications, Challenges, and Opportunities With China Perspective. IEEE Internet of Things Journal 1(4), 349–359 (2014)Google Scholar
  4. 4.
    Montenegro, G., Kushalnagar, N., Hui, J., Culler, D.: Transmission of IPv6 packets over IEEE 802.15.4 networks. In: Internet Proposed Standard RFC 4944 (2007)Google Scholar
  5. 5.
    Winter, I.T., Thubert, P., Brandt, A., Hui, J., Kelsey, R.: RPL: IPv6 routing protocol for low power and lossy networks. In: IETF Request for Comments 6550 (2012)Google Scholar
  6. 6.
    Gaddour, O., Koubaa, A.: RPL in a nutshell: A survey. Elsevier Compueter Networks 56(14) (2012)Google Scholar
  7. 7.
    The Minimum Rank with Hysteresis Objective Function.
  8. 8.
    The ETX Objective Function for RPL.
  9. 9.
    Colistra, G., Pilloni, V., Atzori, L.: Objects that agree on task frequency in the IoT: A lifetime-oriented consensus based approach. In: IEEE World Forum on Internet of Things (WF-IoT), pp. 383–387 (2014)Google Scholar
  10. 10.
    Kafi, M.A., Djenouri, D., Ben-Othman, J., Badache, N.: Congestion Control Protocols in Wireless Sensor Networks: A Survey. IEEE Communications Surveys and Tutorials 16(3), 1369–1390 (2014)zbMATHCrossRefGoogle Scholar
  11. 11.
    Tavakoli, M.: HYDRO: A hybrid routing protocol for lossy and low power networks. In: IETF Internet Draft: draft-tavakoli-hydro-01 (2009)Google Scholar
  12. 12.
    Kim, K., Yoo, S., Park, J., Park, S.D., Lee, J.: Hierarchical routing over 6LoWPAN (HiLow). In: IETF: Internet Draft: draft-deniel-6lowpan-hilow-hierarchical-routing-00.txt, vol. 38 (2005)Google Scholar
  13. 13.
    Kim, K., Park, S., Chakeres, I., Perkins, C.: Dynamic MANET on-demand for 6LoWPAN (DYMO-low) routing. In: Internet Draft: draft- montenegro-6lowpan-dymo-low-routing-03 (2007)Google Scholar
  14. 14.
  15. 15.
    Routing Over Low Power and Lossy Networks (ROLL).
  16. 16.
    Han, B., Lee, S.: Efficient packet error rate estimation in wireless networks. In: Testbeds and Research Infrastructure for the Development of Networks and Communities (TridentCom) (2007)Google Scholar
  17. 17.
    Wireless medium access control (MAC) and physical layer (PHY) specications for low-rat wireless personal area networks (LR-WPANs). In: IEEE 802.15.4 Standard, Part 15.4 (2003)Google Scholar
  18. 18.
    Objective Function Zero for the Routing Protocol for Low-Power and Lossy Networks (RPL).
  19. 19.
    Abreu, C., Ricardo, M., Mendes, P.M.: Energy-aware routing for biomedical wireless sensor networks. Journal of Network and Computer Applications 40, 270–278 (2014)CrossRefGoogle Scholar
  20. 20.
    RPL: IPv6 Routing Protocol for Low-Power and Lossy Networks.
  21. 21.
    Wu, D.: QoS provisioning in wireless networks. In: Wireless Communications and Mobile Computing (2005)Google Scholar
  22. 22.
    Osterlind, F., Dunkel, A., Eriksson, J., Finne, N.: Cross-Level sensor network simulation with COOJA. In: 31st IEEE Conference on Local Compueter Networks, pp. 641–648 (2006)Google Scholar
  23. 23.
    Dunkels, A., Gronvall, B., Voigt, T.: Contiki - a lightweight and flexible operating system for tiny networked sensors. In: 29th Annual IEEE International Conference on Local Computer Networks, pp. 455–462(2004)Google Scholar
  24. 24.
    Aljawawdeh, H., Almomani, I.: Dynamic load balancing protocol (DLBP) for wireless sensor networks. In: IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies (AEECT), pp. 1–6 (2013)Google Scholar
  25. 25.
    Del-Valle-Soto, C., Mex-Perera, C., Orozco-Lugo, A., Galvan-Tejada, G.M., Olmedo, O., Lara, M.: An efficient multi-parent hierarchical routing protocol for WSNs. In: Wireless Telecommunications Symposium (WTS), pp. 1–8 (2014)Google Scholar
  26. 26.
    Rahmani, A.M., Kamali, I., Lotfi-Kamran, P., Afzali-Kusha, A.: Negative exponential distribution traffic pattern for power/performance analysis of network on chips. In: 22nd International Conference on VLSI Design, pp. 157–162 (2009)Google Scholar
  27. 27.
    Clausen, T., Verdiere, A.C., Jiazi, Y.: Performance analysis of Trickle as a flooding mechanism. In: 15th IEEE International Conference on Communication Technology (ICCT), pp. 565–572 (2013)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Computer EngineeringIstanbul Technical UniversityIstanbulTurkey

Personalised recommendations