Congestion control and energy-balanced scheme based on the hierarchy for WSNs

Congestion control and energy-balanced scheme based on the hierarchy for WSNs

For access to this article, please select a purchase option:

Buy article PDF
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
IET Wireless Sensor Systems — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

The problem of congestion control with balanced-energy is important for application of WSNs, since the limited resources and many-to-one communication model often result in congestion and unbalanced energy consumption. In this study, a hierarchy-based congestion control and energy-balanced scheme is proposed. The network model is firstly initialised into a hierarchical topology, by which these neighbour nodes of a node will be explicitly divided into three kinds, i.e., the same hierarchical nodes, the upstream nodes, and the downstream nodes. Then, in the proposed congestion avoidance method, the node will use other lower hierarchy neighbour nodes to forward data when its downstream node will be congested. After that, the congestion control mechanism will detect the congestion via the queue length, forwarding and receiving rate, and inform its upstream nodes to find other next hop to release the congestion. The balanced energy consumption strategy will balance the energy consumption of lower hierarchy nodes by using the node with the most remaining energy. Meanwhile, by using the same hierarchy nodes, the remaining energy of all the nodes in the same hierarchy is balanced. Simulation results show that the proposed algorithm can effectively deal with the network congestion and unbalanced energy consumption.


    1. 1)
      • 1. Rahman, K.C.: ‘A survey on sensor network’, J. Comput. Inf. Technol., 2010, 1, (1), pp. 7687.
    2. 2)
      • 2. Yick, J., Mukherjee, B., Ghosal, D.: ‘Wireless sensor network survey’, Comput. Netw., 2008, 52, (12), pp. 22922330.
    3. 3)
      • 3. Wang, C., Sohraby, K., Li, B., et al: ‘A survey of transport protocols for wireless sensor networks’, IEEE Netw., 2006, 20, (3), pp. 3440.
    4. 4)
      • 4. Ghaffari, A.: ‘Congestion control mechanisms in wireless sensor networks: a survey’, J. Netw. Comput. Appl., 2015, 52, pp. 101115.
    5. 5)
      • 5. Flora, J.: ‘A survey on congestion control techniques in wireless sensor networks’. Int. Conf. on Emerging Trends in Electrical and Computer Technology, 2011.
    6. 6)
      • 6. Kafi, M.A., Djenouri, D., Ben-Othman, J., et al: ‘Congestion control protocols in wireless sensor networks: a survey’, IEEE Commun. Surv. Tutor., 2014, 16, (3), pp. 13691390.
    7. 7)
      • 7. Sergiou, C., Vassiliou, V.: ‘Alternative path creation vs data rate reduction for congestion mitigation in wireless sensor networks’. Proc. of the 9th ACM/IEEE Int. Conf. on Information Processing in Sensor Networks, 2010.
    8. 8)
      • 8. Ansari, M.S., Mahani, A., Kavian, Y.S.: ‘Energy-efficient network design via modelling: optimal designing point for energy, reliability, coverage and end-to-end delay’, Netw. IET, 2013, 2, (1), pp. 1118.
    9. 9)
      • 9. Li, J., Mohapatra, P.: ‘Analytical modeling and mitigation techniques for the energy hole problem in sensor networks’, Pervasive Mob. Comput., 2007, 3, (3), pp. 233254.
    10. 10)
      • 10. Stojmenovic, I., Olariu, S.: ‘Data-centric protocols for wireless sensor networks’. Handbook of Sensor networks, John Wiley & Sons, NJ, USA, 2005, pp. 417456.
    11. 11)
      • 11. Kleerekoper, A., Filer, N.P.: ‘DECOR: distributed construction of load balanced routing trees for many to one sensor networks’, Ad Hoc Netw., 2014, 16, pp. 225236.
    12. 12)
      • 12. Karim, L., Nasser, N.: ‘Reliable location-aware routing protocol for mobile wireless sensor networks’, IET Commun., 2012, 6, (14), pp. 21492158.
    13. 13)
      • 13. Gagarin, A., Hussain, S., Yang, L.T.: ‘Distributed hierarchical search for balanced energy consumption routing spanning trees in wireless sensor networks’, J. Parallel Distrib. Comput., 2010, 70, (9), pp. 975982.
    14. 14)
      • 14. Khedr, M.A, Omar, D.M.: ‘SEP-CS: effective routing protocol for heterogeneous wireless sensor networks’, Ad Hoc Sensor Wirel. Netw., 2015, 26, pp. 211234.
    15. 15)
      • 15. Wang, G., Liu, K.: ‘Upstream hop-by-hop congestion control in wireless sensor networks’. IEEE Int. Symp. on Personal, Indoor and Mobile Radio Communications, Tokyo, Japan, 2009, pp. 14061410.
    16. 16)
      • 16. Annie, U.R., Kasmir Raja, S.V., Antony, J., et al: ‘Energy-efficient predictive congestion control for wireless sensor networks’, IET Wirel. Sens. Syst., 2015, 5, (3), pp. 115123.
    17. 17)
      • 17. Antoniou, P., Pitsillides, A.: ‘A bio-inspired approach for streaming applications in wireless sensor networks based on the Lotka–Volterra competition model’, Comput. Commun., 2010, 33, (17), pp. 20392047.
    18. 18)
      • 18. Yin, X., Zhou, X., Huang, R., et al: ‘A fairness-aware congestion control scheme in wireless sensor networks’, IEEE Trans. Veh. Technol., 2009, 58, (9), pp. 52255234.
    19. 19)
      • 19. Sergiou, C., Vassiliou, V., Paphitis, A.: ‘Hierarchical tree alternative path (HTAP) algorithm for congestion control in wireless sensor networks’, Ad Hoc Netw., 2013, 11, (1), pp. 257272.
    20. 20)
      • 20. Antoniou, P., Pitsillides, A., Blackwell, T., et al: ‘Congestion control in wireless sensor networks based on bird flocking behavior’, Comput. Netw., 2013, 57, (5), pp. 11671191.
    21. 21)
      • 21. Sergiou, C., Vassiliou, V., Paphitis, A.: ‘Congestion control in wireless sensor networks through dynamic alternative path selection’, Comput. Netw., 2014, 75, pp. 226238.

Related content

This is a required field
Please enter a valid email address