Advertisement

A Hole Detour Scheme Using Virtual Position Based on Residual Energy for Wireless Sensor Networks

  • Zeehan Son
  • Myungsu Cha
  • Min Han Shon
  • Moonseong Kim
  • Mihui Kim
  • Hyunseung Choo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6786)

Abstract

Wireless Sensor Networks (WSNs) consist of a large number of low powered nodes that need to operate for months unattended. Since modern WSNs are used in various applications, their topology is becoming complicated. Due to limited precision of deployment, holes may occur in the network, which often lead traditional Greedy Forwarding algorithms to fail. Thus, bypassing the holes is one of the important issues for WSNs. Since each node has limited energy, its energy consumption needs to be optimized to prolong network lifetime. In the well-known Virtual Position (ViP) scheme, each node routes data using virtual positions instead of actual geographic positions to improve the packet delivery rate. A Hole-bypassing Routing with Context-awareness scheme achieves balanced energy consumption by changing current path to one of the candidate paths, based on the residual energy of nodes. However, this scheme tends to extend the size of holes. Since existing hole detour schemes that do not consider efficient energy consumption, they cause imbalanced energy consumption and make network lifetime relatively shorter than other hole detour schemes. Similar to ViP, our scheme uses virtual positions to bypass holes. However, the virtual positions are computed using both geographic positions and the residual energies of neighbor nodes. Our approach outperforms the ViP scheme in terms of network lifetime and hole extension.

Keywords

Hole detouring greedy forwarding geographic routing virtual position 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Finn, G.G.: Routing and addressing problems in large metropolitan-scale internetworks. Technical Report ISI/RR-87-180, Information Sciences Institute (1987)Google Scholar
  2. 2.
    Warneke, B., Last, M., Liebowitz, B., Kristofer, Pister, S.J.: Smart Dust: Communicating with a Cubic-Millimeter Computer. Computer Magazine 34(1), 44–51 (2001)CrossRefGoogle Scholar
  3. 3.
    Ahmed, N., Kanhere, S.S., Jha, S.: The hole problem in wireless sensor networks: a survey. ACM SIGMOBILE Mobile Computing and Communications Review 9(2) (2005)Google Scholar
  4. 4.
    You, J., Lieckfeldt, D., Han, Q., Salzmann, J., Timmermann, D.: Look-ahead Geographic Routing for Sensor Networks. In: Proceedings of PERCOM (2009)Google Scholar
  5. 5.
    Karp, B., Kung, H.T.: GPSR: Greedy perimeter stateless routing for wireless networks. In: Proceedings of MobiCom, pp. 243–254 (2000)Google Scholar
  6. 6.
    Jia, W., Wang, T., Wang, G., Guo, M.: Hole Avoiding in Advance Routing in Wireless Sensor Networks. In: Proceedings of IEEE WCNC (2007)Google Scholar
  7. 7.
    You, J., Lieckfeldt, D., Reichenbach, F., Timmermann, D.: Context-aware Geographic Routing for Sensor Networks with Routing Holes. In: Proceedings of IEEE WCNC (2009)Google Scholar
  8. 8.
    Sheng, X., Hu, Y.: Maximum Likelihood Multiple-Source Localization Using Acoustic Energy Measurements with Wireless Sensor Networks. IEEE Transactions on Signal Processing 53(1) (2005)Google Scholar
  9. 9.
    Niu, R., Varshney, K.: Target Location Estimation in Sensor Networks with Quantized Data. IEEE Transactions on Signal Processing 54(12) (2006)Google Scholar
  10. 10.
    Zhu, J., Chen, S., Bensaou, B., Hung, K.-L.: Tradeoff between lifetime and rate allocation in wireless sensor networks: a cross layer approach. In: Proceedings of IEEE INFOCOM (2007)Google Scholar
  11. 11.
    Texas Intruments. 2.4 GHz IEEE 802.15.4 / ZigBee-Ready RF Transceiver, Rev. B (2007), http://focus.ti.com/docs/prod/folders/print/cc2420.html
  12. 12.
    Tang, J., Xue, G.: Node-disjoint path routing in wireless networks: tradeoff between path lifetime and total energy. In: Proceedings of IEEE ICC, pp. 3812–3816 (2004)Google Scholar
  13. 13.
    Maleki, M., Dantu, K., Pedram, M.: Lifetime prediction routing in mobile ad hoc networks. In: Proceedings of IEEE WCNC (2003)Google Scholar
  14. 14.
    Xu, Y., Heidemann, J.S., Estrin, D.: Geography-informed energy conservation for ad hoc routing. In: Proceedings of MOBICOM, pp. 70–84 (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Zeehan Son
    • 1
  • Myungsu Cha
    • 1
  • Min Han Shon
    • 1
  • Moonseong Kim
    • 2
  • Mihui Kim
    • 3
  • Hyunseung Choo
    • 1
  1. 1.School of Information and Communication EngineeringSungkyunkwan UniversitySuwonKorea
  2. 2.Information and Communications Examination BureauKorean Intellectual Property OfficeDaejeonKorea
  3. 3.Department of Computer EngineeringHankyong National UniversityAnseongKorea

Personalised recommendations