Advertisement

All Is Not Lost: Understanding and Exploiting Packet Corruption in Outdoor Sensor Networks

  • Frederik Hermans
  • Hjalmar Wennerström
  • Liam McNamara
  • Christian Rohner
  • Per Gunningberg
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8354)

Abstract

During phases of transient connectivity, sensor nodes receive a substantial number of corrupt packets. These corrupt packets are generally discarded, losing the sent information and wasting the energy put into transmitting and receiving. Our analysis of one year’s data from an outdoor sensor network deployment shows that packet corruption follows a distinct pattern that is observed on all links. We explain the pattern’s core features by considering implementation aspects of low-cost 802.15.4 transceivers and independent transmission errors. Based on the insight into the corruption pattern, we propose a probabilistic approach to recover information about the original content of a corrupt packet. Our approach vastly reduces the uncertainty about the original content, as measured by a manifold reduction in entropy.We conclude that the practice of discarding all corrupt packets in an outdoor sensor network may be unnecessarily wasteful, given that a considerable amount of information can be extracted from them.

Keywords

wireless transmission errors packet corruption outdoor sensor networks robustness 802.15.4 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Lin, S., Zhang, J., Zhou, G., Gu, L., Stankovic, J.A., He, T.: ATPC: adaptive transmission power control for wireless sensor networks. CM SenSys 2006 (2006)Google Scholar
  2. 2.
    Wennerström, H., Hermans, F., Rensfelt, O., Rohner, C., Nordén, L.A.: A Long-Term Study of Correlations between Meteorological Conditions and 802.15.4 Link Performance. In: IEEE SECON 2013 (2013)Google Scholar
  3. 3.
    Schmidt, F., Ceriotti, M., Wehrle, K.: Bit Error Distribution and Mutation Patterns of Corrupted Packets in Low-Power Wireless Networks. In: WiNTECH 2013 (2013)Google Scholar
  4. 4.
    Liang, C.J.M., Priyantha, N.B., Liu, J., Terzis, A.: Surviving Wi-Fi Interference in Low Power ZigBee Networks. In: ACM SenSys 2010 (2010)Google Scholar
  5. 5.
    Hermans, F., Rensfelt, O., Voigt, T., Ngai, E., Nordén, L.A., Gunningberg, P.: SoNIC: Classifying Interference in 802.15.4 Sensor Networks. In: IPSN 2013 (2013)Google Scholar
  6. 6.
    Jamieson, K., Balakrishnan, H.: PPR: partial packet recovery for wireless networks. In: ACM SIGCOMM 2007 (2007)Google Scholar
  7. 7.
    Hauer, J.-H., Willig, A., Wolisz, A.: Mitigating the Effects of RF Interference through RSSI-Based Error Recovery. In: Silva, J.S., Krishnamachari, B., Boavida, F. (eds.) EWSN 2010. LNCS, vol. 5970, pp. 224–239. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  8. 8.
    Dubois-Ferrière, H., Estrin, D., Vetterli, M.: Packet combining in sensor networks. In: ACM SenSys 2005 (2005)Google Scholar
  9. 9.
    Texas Instruments Inc.: CC2420 - 2.4 GHz IEEE 802.15.4, ZigBee-ready RF Transceiver, http://www.ti.com/lit/gpn/cc2420
  10. 10.
    IEEE Computer Society: 802.15.4: Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low-Rate Wireless Personal Area Networks (WPANs)Google Scholar
  11. 11.
    Wu, X., Liu, M.: In-situ soil moisture sensing: measurement scheduling and estimation using compressive sensing. In: ACM/IEEE IPSN 2012 (2012)Google Scholar
  12. 12.
    Srinivasan, K., Dutta, P., Tavakoli, A., Levis, P.: An empirical study of low-power wireless. ACM Trans. Sen. Netw. 6(2) (March 2010)Google Scholar
  13. 13.
    Baccour, N., Koubâa, A., Mottola, L., Zúñiga, M.A., Youssef, H., Boano, C.A., Alves, M.: Radio link quality estimation in wireless sensor networks: A survey. ACM Trans. Sen. Netw. 8(4) (September 2012)Google Scholar
  14. 14.
    Schmid, T.: GNU Radio 802.15.4 En- and Decoding. Technical report, Department of Electrical Engineering, University of California, Los Angeles 2006 (2006)Google Scholar
  15. 15.
    Xiong, F.: Digital Modulation Techniques, 2nd edn. Artech House (April 2006)Google Scholar
  16. 16.
    Kong, L., Xia, M., Liu, X.Y., Wu, M.Y., Liu, X.: Data loss and reconstruction in sensor networks. In: IEEE INFOCOM 2013 (2013)Google Scholar
  17. 17.
    Hasenfratz, D., Saukh, O., Thiele, L.: Model-driven accuracy bounds for noisy sensor readings. In: IEEE DCOSS 2013 (2013)Google Scholar
  18. 18.
    Notor, J., Caviglia, A., Levy, G.: CMOS RFIC Architectures for IEEE 802.16.4 Networks. Technical report, Cadence Design Systems, Inc. 2003 (2003)Google Scholar
  19. 19.
    Zúñiga Zamalloa, M., Krishnamachari, B.: An analysis of unreliability and asymmetry in low-power wireless links. ACM Trans. Sen. Netw. 3(2) (June 2007)Google Scholar
  20. 20.
    Han, B., Ji, L., Lee, S., Bhattacharjee, B., Miller, R.R.: Are All Bits Equal? Experimental Study of IEEE 802.11 Communication Bit Errors. IEEE/ACM Trans. Netw. 20(6) (2012)Google Scholar
  21. 21.
    Wu, K., Tan, H., Ngan, H.L., Liu, Y., Ni, L.: Chip Error Pattern Analysis in IEEE 802.15.4. IEEE Trans. Mob. Comp. 11(4) (2012)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Frederik Hermans
    • 1
  • Hjalmar Wennerström
    • 1
  • Liam McNamara
    • 1
  • Christian Rohner
    • 1
  • Per Gunningberg
    • 1
  1. 1.Uppsala UniversitetSweden

Personalised recommendations