Avoiding energy-compromised hotspots in resource-limited wireless networks

  • Joseph Rahmé
  • Aline Carneiro Viana
  • Khaldoun Al Agha
Conference paper
Part of the IFIP — The International Federation for Information Processing book series (IFIPAICT, volume 256)


The vast literature on the wireless sensor research community contains many valuable proposals for managing energy consumption, the most important factor that determines sensors lifetime. Interesting researches have been facing this requirement by focusing on the extension of the entire network lifetime: either by switching between node states (active, sleep), or by using energy efficient routing. We argue that a better extension of the network lifetime can be obtained if an efficient combination of management mechanisms can be performed at the energy of each single sensor and at the load distribution over the network. Considering these two accuracy levels (i.e., node and network), dis paper presents a new approach that uses cost functions to choose energy efficient routes. In particular, by making different energy considerations at a node level, our approach distributes routing load, avoiding thus, energy-compromised hotspots that may cause network disconnections. The proposed cost functions have completely decentralized and adaptive behavior and take into consideration: the end-to-end energy consumption, the remaining energy of nodes, and the number of transmissions a node can make before its energy depletion. Our simulation results show that, though slightly increasing path lengths from sensor to sink nodes, the proposed scheme (1) improves significantly the network lifetime for different neighborhood densities degrees, while (2) preserves network connectivity for a longer period of time.


Cost Function Wireless Network Wireless Sensor Network Intermediate Node Network Lifetime 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Agarwal, S., Krishnamurthy, S., Katz, R., Dao, S.: Distributed power control in ad-hoc wireless networks. Proceedings of PIMRC (2001)Google Scholar
  2. 2.
    Cardei, M., Du, D.: Improving wireless sensor network lifetime through power aware organization. ACM Journal of Wireless Networks (2005)Google Scholar
  3. 3.
    Cardei, M., Wu, J., Yang, S.: Topology control in ad hoc wireless networks with hitch-hiking. The First IEEE International Conference on Sensor and Ad hoc Communications and Networks (SECON04 (2004)Google Scholar
  4. 4.
    Carle, J., Simplot-Ryl, D.: Energy-efficient area monitoring for sensor networks. Computer 37, no.2, 40–46 (2004)CrossRefGoogle Scholar
  5. 5.
    Chang, J., Tassiulas, L.: Energy conserving routing in wireless ad-hoc nertworks. IEEE IN-FOCOM 2000, Tel Aviv, Israel (2000)Google Scholar
  6. 6.
    Chen, B., Jamieson, K., Balakrishnan, H., Morris, R.: Span: An energy-efficient coordination algorithm for topology maintenance in ad hoc wireless networs. Wireless networks Vol.8 Issue 5 (2002)Google Scholar
  7. 7.
    Culler, D., Estrin, D., Srivastava, M.: Overview of sensor networks. IEEE Computer Society pp. 41–49 (2004)Google Scholar
  8. 8.
    Hassanein, H., Luo, J.: Reliable energy aware routing in wireless sensor networks. Second IEEE Workshop on Dependability and Security in Sensor Networks and Systems DSSNS (2006)Google Scholar
  9. 9.
    Ingelrest, F., Simplot-Ryl, D., Stojmenovic, I.: Optimal transmission radius for energy efficient broadcasting protocols in ad hoc networks. IEEE Transactions on Parallel and Distributed Systems (2006)Google Scholar
  10. 10.
    Kwon, S., Shroff, N.B.: Energy-efficient interference-based routing for multi-hop wireless networks. IEEE INFOCOM 06, Barcelona, Spain (2006)Google Scholar
  11. 11.
    Merrer, E.L., V. Gramoli, A.C.V., Bertier, M., Kermarre, A.M.: Energy aware self-organizing density management in wireless sensor networks. In: ACM MobiShare. Los Angeles, CA (2006)Google Scholar
  12. 12.
    Mirza, D., Owrang, M., Shrugers, C.: Energy-efficient wakeup scheduling for maximizing lifetime of ieee 802.15.4 networks. International Conference on Wireless Internet (WICON’05), Budapest, Hungary (2005)Google Scholar
  13. 13.
    Shah, R., Rabaey, J.: Energy aware routing for low energy ad hoc sensor networks. Proceedings of IEEE Wireless Communications and Networking conference (WCNC) 1, 17–21 (2002)Google Scholar
  14. 14.
    Shresta, N.: Reception awamess for energy conservation in ad hoc networks. PhD, Macquarie University Sydney, Australia (2006)Google Scholar
  15. 15.
    Xu, Y., Heidemann, J., Estrin, D.: Geography-informed energy conservation for ad hoc routing. Proceedings of the 7th annual international conference on Mobile computing and networking, Rome, Italy (2001)Google Scholar
  16. 16.
    Zhang, B., Mouftah, H.: Energy-aware on-demand routing protocols for wireless ad hoc networks. Wireless Networks 12 Issue 4 (2006)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2008

Authors and Affiliations

  • Joseph Rahmé
    • 1
  • Aline Carneiro Viana
    • 2
  • Khaldoun Al Agha
    • 1
  1. 1.LRIUniversité Paris-SUD XIParisFrance
  2. 2.ASAPINRIA SaclayIle de France sudFrance

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