Wireless Networks

, Volume 21, Issue 2, pp 485–498 | Cite as

An energy efficient joint localization and synchronization solution for wireless sensor networks using unmanned aerial vehicle

  • Leandro A. Villas
  • Daniel L. Guidoni
  • Guilherme Maia
  • Richard W. Pazzi
  • Jó Ueyama
  • Antonio A. F. Loureiro
Article

Abstract

Localization and synchronization are fundamental services for many applications in wireless sensor networks (WSNs), since it is often required to know the sensor nodes’ position and global time to relate a given event detection to a specific location and time. However, the localization and synchronization tasks are often performed after the sensor nodes’ deployment on the sensor field. Since manual configuration of sensor nodes is usually an impractical activity, it is necessary to rely on specific algorithms to solve both localization and clock synchronization problems of sensor nodes. With this in mind, in this work we propose a joint solution for the problem of 3D localization and time synchronization in WSNs using an unmanned aerial vehicle (UAV). A UAV equipped with GPS flies over the sensor field broadcasting its geographical position. Therefore, sensor nodes are able to estimate their geographical position and global time without the need of equipping them with a GPS device. Through simulation experiments, we show that our proposed joint solution reduces time synchronization and localization errors as well as energy consumption when compared to solutions found in the literature.

Keywords

Energy efficient Wireless sensor networks Unmanned aerial vehicle Localization Synchronization problems 

References

  1. 1.
    Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cyirci, E. (2002). Wireless sensor networks: A survey. Computer Networks, 38(4), 393–422.CrossRefGoogle Scholar
  2. 2.
    Jiang, X., Polastre, J., & Culler, D. (2005). Perpetual environmentally powered sensor networks. In IPSN ’05 (pp. 1–10).Google Scholar
  3. 3.
    Zeng, K., Ren, K., Lou, W., & Moran, P. J. (2009). Energy aware efficient geographic routing in lossy wireless sensor networks with environmental energy supply. Wireless Network, 15(1), 39–51.CrossRefGoogle Scholar
  4. 4.
    Liu, R. S., Fan, K. W., Zheng, Z., & Sinha, P. (2011). Perpetual and fair data collection for environmental energy harvesting sensor networks. IEEE/ACM Transactions on Networking, 19(4), 947–960.CrossRefGoogle Scholar
  5. 5.
    Boukerche, A. (2008). Algorithms and protocols for wireless sensor networks. Hoboken: WileyCrossRefGoogle Scholar
  6. 6.
    Akkaya, K., & Younis, M. (2005). A survey on routing protocols for wireless sensor networks. Ad Hoc Networks, 3(3), 325–349.CrossRefGoogle Scholar
  7. 7.
    Villas, L. A., Boukerche, A., Guidoni, D. L., de Oliveira, H. A., de Araujo, R. B., & Loureiro, A. A. (2013). An energy-aware spatio-temporal correlation mechanism to perform efficient data collection in wireless sensor networks. Computer Communications, 36(9), 1054–1066.CrossRefGoogle Scholar
  8. 8.
    Albowicz, J., Chen, A., & Zhang, L. (2001). Recursive position estimation in sensor networks. In ICNP ’01 (pp. 35–41).Google Scholar
  9. 9.
    Niculescu, D., & Nath, B. (2003). Ad hoc positioning systems (aps) using oao. In IEEE INFOCOM ’03 (pp. 1734–1743).Google Scholar
  10. 10.
    Oliveira, H. A. B. F., Boukerche, A., Nakamura, E. F., & Loureiro, A. A. F. (2009). Localization in time and space for wireless sensor networks: An efficient and lightweight algorithm. Performance Evaluation, 66(3–5), 209–222.CrossRefGoogle Scholar
  11. 11.
    Gupta, P., & Kumar, P. (2000). The capacity of wireless networks. IEEE Transactions on Information Theory, 46(2), 388–404.CrossRefMATHMathSciNetGoogle Scholar
  12. 12.
    Wang, G., & Yang, K. (2011). A new approach to sensor node localization using rss measurements in wireless sensor networks. IEEE Transactions on Wireless Communication, 10(5), 1389–1395.CrossRefGoogle Scholar
  13. 13.
    Ma, D., Er, M. J., & Wang, B. (2010). Analysis of hop-count-based source-to-destination distance estimation in wireless sensor networks with applications in localization. IEEE Transactions on Vehicular Technology, 59(6), 2998–3011.CrossRefGoogle Scholar
  14. 14.
    Guidoni, D. L., Boukerche, A., Villas, L. A., Souza, F. S. H., de Oliveira, H. A. B. F., & Loureiro, A. A. F. (2012). A small world approach for scalable and resilient position estimation algorithms for wireless sensor networks. In MOBIWAC ’12 (pp. 71–78).Google Scholar
  15. 15.
    Galstyan, A., Krishnamachari, B., Lerman, K., & Pattem, S. (2009). Distributed online localization in sensor networks using a moving target. In IPSN ’09 (pp. 61–70).Google Scholar
  16. 16.
    Deak, G., Curran, K., & Condell, J. (2012). A survey of active and passive indoor localisation systems. Computer Communications, 35(16), 1939–1954.CrossRefGoogle Scholar
  17. 17.
    He, Y., Liu, Y., Shen, X., Mo, L., & Dai, G. (2013). Noninteractive localization of wireless camera sensors with mobile beacon. IEEE Transactions on Mobile Computing, 12(2), 333–345.CrossRefGoogle Scholar
  18. 18.
    Yao, H., & Zhou, W. (2010). Synchronization algorithm for multi-hop in wireless sensor networks. In CIS ’10 (pp. 28–32).Google Scholar
  19. 19.
    Maróti, M., Kusy, B., Simon, G., & Lédeczi, A. (2004). The flooding time synchronization protocol. In SenSys ’04 (pp. 39–49).Google Scholar
  20. 20.
    Liu, Y., Li, J., & Guizani, M. (2012) Lightweight secure global time synchronization for wireless sensor networks. In IEEE WCNC ’12 (pp. 2312–2317).Google Scholar
  21. 21.
    Sinan Yldrm, K., & Kantarc, A. (2014). Time synchronization based on slow flooding in wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 25(1), 244–253.CrossRefGoogle Scholar
  22. 22.
    Wu, Y. C., Chaudhari, Q., & Serpedin, E. (2011). Clock synchronization of wireless sensor networks. IEEE Signal Processing Magazine, 28(1), 124–138.CrossRefGoogle Scholar
  23. 23.
    Wu, J., Jiao, L., & Ding, R. (2012). Average time synchronization in wireless sensor networks by pairwise messages. Computer Communications, 35(2), 221–233.CrossRefGoogle Scholar
  24. 24.
    Mica2 crossbow technology. Mica2 DataSheet. Document Part Number: 6020-0042-0. Resource document. http://www.eol.ucar.edu/isf/facilities/isa/internal/CrossBow/DataSheets/mica2.pdf. Accessed 2 Aug 2014.
  25. 25.
    Lenzen, C., Sommer, P., & Wattenhofer, R. (2009). Optimal clock synchronization in networks. In SenSys ’09 (pp. 225–238).Google Scholar
  26. 26.
    Li, Q., & Rus, D. (2006). Global clock synchronization in sensor networks. IEEE Transactions Computers, 55(2), 214–226.CrossRefGoogle Scholar
  27. 27.
    Golub, G. H., & Loan, C. F. V. (1996). Matrix Computations (3rd ed.). Baltimore, MD: Johns Hopkins University Press.MATHGoogle Scholar
  28. 28.
    Sundararaman, B., Buy, U., & Kshemkalyani, A. D. (2005). Clock synchronization for wireless sensor networks: a survey. Ad Hoc Networks, 3(3), 281–323.CrossRefGoogle Scholar
  29. 29.
    Elson, J., Girod, L., & Estrin, D. (2002). Fine-grained network time synchronization using reference broadcasts. SIGOPS Operating Systems Review, 36, 147–163.CrossRefGoogle Scholar
  30. 30.
    Micaz crossbow technology. MicaZ DataSheet. Document Part Number: 6020-0060-04 Rev A. Resource document. http://www.openautomation.net/uploadsproductos/micaz_datasheet.pdf. Accessed 2 Aug 2014.
  31. 31.
    Distributed Computing Group, ETH Zurich. Sinalgo: Simulator for network algorithms. http://dcg.ethz.ch/projects/sinalgo. Accessed 2 Aug 2014.

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Leandro A. Villas
    • 1
  • Daniel L. Guidoni
    • 2
  • Guilherme Maia
    • 3
  • Richard W. Pazzi
    • 4
  • Jó Ueyama
    • 5
  • Antonio A. F. Loureiro
    • 3
  1. 1.Institute of ComputingUniversity of CampinasCampinasBrazil
  2. 2.Computer Science DepartmentFederal University of São João del-ReiSão João del ReiBrazil
  3. 3.Computer Science DepartmentFederal University of Minas GeraisBelo HorizonteBrazil
  4. 4.Information TechnologyUniversity of Ontario Institute of TechnologyOshawaCanada
  5. 5.Institute of Mathematics and Computer ScienceUniversity of São PauloSão PauloBrazil

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