ACO Based Energy-Balance Routing Algorithm for WSNs

  • Xuepeng Jiang
  • Bei Hong
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6145)


Ant Colony Optimization (ACO) is a heuristic bionic evolutive algorithm. In ACO algorithm, every ant has simple function, works with simple principle, which suits the characteristic of Wireless Sensor Networks (WSNs) and the request of its routing design. An ACO based Energy-Balance Routing Algorithm(ABEBR) was presented to balance the energy consumption in WSNs. Furthermore, a new pheromone update operator was designed to integrate energy consumption and hops into routing choice. This paper compares ABEBR with some classic routing algorithms (LEACH, DD and Flooding). Simulation results show that the presented algorithm can avoid energy working out too early on the less hops path, obviously balance the energy consumption and prolong the lifetime of WSNs.


Ant Colony Optimization WSNs routing algorithm Energy Balance Pheromone 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Wang, Z., Crowcroft, J.: Quality of Service Routing for Supporting Multimedia Applications. IEEE Journal on Selected Areas in Communications 14(7), 1228–1234 (1996)CrossRefGoogle Scholar
  2. 2.
    Duan, H.B.: Ant Colony Algorithm: Theory and Applications, pp. 24–26 (2005)Google Scholar
  3. 3.
    Zhang, Y., Kuhn, L., Fromherz, M.: Improvements on Ant Routing for Sensor Networks. In: Dorigo, M., Birattari, M., Blum, C., Gambardella, L.M., Mondada, F., Stützle, T. (eds.) ANTS 2004. LNCS, vol. 3172, pp. 154–165. Springer, Heidelberg (2004)Google Scholar
  4. 4.
    Singh, G., Das, S., Gosavi, S., Pujar, S.: Ant Colony Algorithms for Steiner Trees: An Application to Routing in Sensor Networks. In: Recent Developments in Biologically Inspired Computing, pp. 181–206. Idea Group Publishing (2004)Google Scholar
  5. 5.
    Alonso, J., Dunkels, A., Voigt, T.: Bounds on the energy consumption of routings in wireless sensor nodes. In: WiOpt 2004: Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks, Cambridge, UK (2004)Google Scholar
  6. 6.
    Al-Karaki, J.N., Kamal, A.E.: Routing Techniques in Wireless Sensor Networks: A Survey. In: Wireless Communications, pp. 6–28. IEEE, Los Alamitos (2004)Google Scholar
  7. 7.
    Madiraju, S., Mallanda, C.: EBRP: Energy Band based Routing Protocol for Wireless Sensor Networks. In: Intelligent Sensors, Sensor Networks and Information Processing Conference (2004)Google Scholar
  8. 8.
    Min, R., Bhardwaj, M., Cho, S.-H., Shih, E., Sinha, A., Wang, A., Chandrakasan, A.: Low-Power Wireless Sensor Networks. In: The 14th International Conference on VLSI Design, p. 205 (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Xuepeng Jiang
    • 1
  • Bei Hong
    • 2
  1. 1.Department of Strategic Missile EngineeringNaval Aeronautical and Astronautical UniversityYantaiChina
  2. 2.Xi’an Institute of Hi-TechXi’anChina

Personalised recommendations