Skip to main content

Advertisement

SpringerLink
Log in

Locally Optimal Source Routing for energy-efficient geographic routing

  • Published:
Wireless Networks Aims and scope Submit manuscript

Abstract

We analyze the problem of finding an energy-efficient path from a source node to a destination using geographic routing. Existing schemes have neglected the fact that neighbors which are not closer to the destination than the current node can still reduce energy consumption by taking part in the selected path. Moreover, recent works have confirmed that the generally used Unit Disk Graph to model Wireless Sensor Networks does not represent accurately the behavior of real links. We propose a new scheme called Locally Optimal Source Routing (LOSR) that is able to use neighbors which do not provide advance toward the destination to reduce the overall energy consumption while still avoiding routing loops. Using an Automatic Repeat reQuest (ARQ) mechanism hop by hop we overcome the problems caused by errors in radio transmissions and we introduce a novel routing metric, which accounts for those errors in the energy consumption. Our simulation results show that the proposed scheme outperforms existing solutions over a variety of scenarios and network densities.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Bondy, J. A., & Murty, U. S. R. (1976). Graph theory with applications. London: Macmillan.

    Google Scholar 

  2. Bose, P., Morin, P., Stojmenovic, I., & Urrutia, J. (2001). Routing with guaranteed delivery in ad hoc wireless networks. Wireless Networks, 7(6), 609–616.

    Article  MATH  Google Scholar 

  3. Datta, S., Stojmenovic, I., & Wu, J. (2001). Internal node and shortcut based routing with guaranteed delivery in wireless networks. In Proc. 21st international conference on distributed computing systems (ICDCSW ’01) (p. 461). Washington, DC, USA: IEEE Computer Society.

  4. Finn, G. G. (1987). Routing and Addressing Problems in Large Metropolitan-Scale Internetworks. Tech. Rep. ISI/RR-87-180, University of Southern California, Information Sciences Institute.

  5. Gabriel, K., & Sokal, R. (1969). A new statistical approach to geographic variation analysis. Systematic Zoology, 18, 259–278.

    Article  Google Scholar 

  6. Giordano, S., Stojmenovic, I., & Blazevic, L. (2004). Position based routing algorithms for ad hoc networks: A taxonomy. In X.␣Cheng, X. Huang, & D. Z. Du (Eds.), Ad hoc wireless networking (pp. 103–136). Kluwer.

  7. Haque, I. T., Assi, C., & Atwood, J. W. (2005). Randomized energy aware routing algorithms in mobile ad hoc networks. In Proc. 8th ACM International Symposium on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM ’05) (pp. 71–78). New York, NY, USA: ACM Press.

  8. Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless microsensor networks. In Proc. 33rd Annual Hawaii International Conference on System Sciences (HICSS ’00).

  9. Hou, T.-C. & Victor Li (1986). Transmission range control in multihop packet radio networks. IEEE Transactions on Communications [legacy, pre-1988], 34(1), 38–44.

    Google Scholar 

  10. Karl, H., & Willig, A. (2005). Protocols and architectures for wireless sensor networks. John Wiley & Sons.

  11. Karp, B., & Kung, H. T. (2000) GPSR: greedy perimeter stateless routing for wireless networks. In Proc. 6th Annual ACM/IEEE International Conference on Mobile Computing and Networking (MobiCom ’00) (pp. 243–254). New York, NY, USA: ACM Press.

  12. Kuruvila, J., Nayak, A., & Stojmenovic, I. (2001). Progress and location based localized power aware routing for ad hoc and sensor wireless networks. IEEE Transactions on Parallel and Distributed Systems, 12(11), 1122–1133.

    Article  Google Scholar 

  13. Kuruvila, J., Nayak, A., & Stojmenovic, I. (2005). Hop count optimal position based packet routing algorithms for ad hoc wireless networks with a realistic physical layer. IEEE Journal on Selected Areas in Communications, 23(6), 1267–1275.

    Article  Google Scholar 

  14. Kuruvila, J., Nayak, A., Stojmenovic, I. (2006). Greedy localized routing for maximizing probability of delivery in wireless ad hoc networks with a realistic physical layer. Journal of Parallel Distributed Computing, 66(4), 499–506.

    Article  MATH  Google Scholar 

  15. Lee, S., Bhattacharjee, B., & Banerjee, S. (2005). Efficient geographic routing in multihop wireless networks. In Proc. 6th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc ’05), pp. 230–241.

  16. Pottie, G. J., & Kaiser, W. J. (2000). Wireless integrated network sensors. Communications of the ACM, 43(5), 51–58.

    Article  Google Scholar 

  17. Rodoplu, V., & Meng, T. H. (1999). Minimum energy mobile wireless networks. IEEE Journal on Selected Areas in Communications, 17(8), 1333–1344.

    Article  Google Scholar 

  18. Seada, K., Zuniga, M., & Helmy, A., & Krishnamachari, B. (2004). Energy-efficient forwarding strategies for geographic routing in lossy wireless sensor networks. In Proc. 2nd International Conference on Embedded Networked Sensor Systems (SenSys ’04) (pp. 108–121). New York, NY, USA: ACM Press.

  19. Singh, S., Woo, M., & Raghavendra, C. S. (1998). Power-aware routing in mobile ad hoc networks. In Proc. 4th annual ACM/IEEE International Conference on Mobile Computing and Networking (MobiCom ’98) (pp. 181–190). New York, NY, USA: ACM Press.

  20. Stojmenovic, I., & Lin, X. (2001). Power-aware localized routing in wireless networks. IEEE Transactions on Paralell and Distributed Systems, 12(10), 1122–1133.

    Article  Google Scholar 

  21. Toussaint, G. T. (1980). The relative neighborhood graph of a finite planar set. Pattern Recognition, 12, 261–268.

    Article  MATH  MathSciNet  Google Scholar 

  22. Woo, A., Tong, T., & Culler, D. (2003). Taming the underlying challenges of reliable multihop routing in sensor networks. In Proc. First International Conference on Embedded Networked Sensor Systems (SenSys ’03) (pp. 14–27). New York, NY, USA: ACM Press.

  23. Zhao, J., & Govindan, R. (2003). Understanding packet delivery performance in dense wireless sensor networks. In Proc. First International Conference on Embedded Networked Sensor Systems (SenSys ’03) (pp. 1–13). New York, NY, USA: ACM Press.

Download references

Acknowledgments

This work was supported in part by the Spanish MEC by means of the “Ramon y Cajal“ Research Program, and in part by the SMART TIN2005-07705-C02-02 Project.

Author information

Authors and Affiliations

  1. Department of Information and Communications Engineering, Facultad de Informatica, University of Murcia, Campus de Espinardo s/n, Murcia, 30100, Spain

    Juan A. Sanchez & Pedro M. Ruiz

Authors
  1. Juan A. Sanchez
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pedro M. Ruiz
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Juan A. Sanchez.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Sanchez, J.A., Ruiz, P.M. Locally Optimal Source Routing for energy-efficient geographic routing. Wireless Netw 15, 513–523 (2009). https://doi.org/10.1007/s11276-007-0066-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11276-007-0066-1

Keywords

Search

Navigation