Congestion avoidance, detection and alleviation in wireless sensor networks

Abstract

Congestion in wireless sensor networks (WSNs) not only causes severe information loss but also leads to excessive energy consumption. To address this problem, a novel scheme for congestion avoidance, detection and alleviation (CADA) in WSNs is proposed in this paper. By exploiting data characteristics, a small number of representative nodes are chosen from those in the event area as data sources, so that the source traffic can be suppressed proactively to avoid potential congestion. Once congestion occurs inevitably due to traffic mergence, it will be detected in a timely way by the hotspot node based on a combination of buffer occupancy and channel utilization. Congestion is then alleviated reactively by either dynamic traffic multiplexing or source rate regulation in accordance with the specific hotspot scenarios. Extensive simulation results under typical congestion scenarios are presented to illuminate the distinguished performance of the proposed scheme.

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

References

  1. Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E., 2002. A survey on sensor network. IEEE Commun. Mag., 40(8):102–114. [doi:10.1109/MCOM.2002.1024422]

    Article  Google Scholar 

  2. Akan, O.B., Akyildiz, I.F., 2005. Event-to-sink reliable transport in wireless sensor networks. IEEE Trans. Network., 13(5):1003–1016. [doi:10.1109/TNET.2005. 857076]

    Article  Google Scholar 

  3. Berger, J.O., Oliveira, V.D., Sanso, B., 2001. Objective Bayesian analysis of spatially correlated data. J. Am. Statist. Assoc., 96(456):1361–1374. [doi:10.1198/016214501753382282]

    MATH  Article  Google Scholar 

  4. Casella, G., Berger, R.L., 2001. Statistical Inference. Duxbury Press, CA, USA, p.139–203.

    Google Scholar 

  5. Chen, L., Szymanski, B.K., Branch, J.W., 2008. Quality-Driven Congestion Control for Target Tracking in Wireless Sensor Networks. Proc. 5th IEEE Int. Conf. on Mobile Ad Hoc and Sensor Systems, p.766–771. [doi:10.1109/MAHSS.2008.4660115]

  6. Chen, L.J., Low, S.H., Chiang, M., Doyle, J.C., 2006. Cross-Layer Congestion Control, Routing and Scheduling Design in Ad Hoc Wireless Networks. Proc. 25th Int. Conf. on Computer Communications, p.1–13. [doi:10.1109/INFOCOM.2006.142]

  7. Chen, W.P., Hou, J.C., Sha L., 2004. Dynamic clustering for acoustic target tracking in wireless sensor networks. IEEE Trans. Mob. Comput., 3(3):258–271. [doi:10.1109/TMC.2004.22]

    Article  Google Scholar 

  8. Cheng, T.E., Bajcsy, R., 2004. Congestion Control and Fairness for Many-to-One Routing in Sensor Networks. Proc. 2nd Int. Conf. on Embedded Networked Sensor Systems, p.148–161. [doi:10.1145/1031495.1031513]

  9. Das, A., Dutta, D., 2005. Data acquisition in multiple-sink sensor networks. ACM Mob. Comput. Commun. Rev., 9(3):82–85. [doi:10.1145/1094549.1094561]

    Article  Google Scholar 

  10. Du, Z.G., Tong, J., Huang, J.H., Su, Y.M., Yang, X.B., Qian, H.H., Fang, W.W., Wu, J.F., Liu, Y., Qian, D.P., 2007. ProNet: A Wireless Sensor Network Testbed Supporting Performance Measurement and Background Traffic Generation. Proc. 2nd Int. Conf. on the Latest Advances in Networks, p.185–190.

  11. Eisenman, S.B., Campbell, A.T., 2007. E-CSMA: Supporting Enhanced CSMA Performance in Experimental Sensor Networks Using Per-Neighbor Transmission Probability Thresholds. Proc. 26th Int. Conf. on Computer Communications, p.1208–1216. [doi:10.1109/INFCOM.2007.144]

  12. Fang, W.W., Qian, D.P., Liu, Y., 2008. Transmission control protocols for wireless sensor networks. J. Software, 19(6):1439–1451 (in Chinese). [doi:10.3724/SP.J.1001.2008.01439]

    Article  Google Scholar 

  13. Galluccio, L., Campbell, A., Palazzo, S., 2005. CONCERT: Aggregation-Based Congestion Control for Sensor Networks. Proc. 3rd Int. Conf. on Embedded Networked Sensor Systems, p.274–275. [doi:10.1145/1098918.1098951]

  14. Gedik, B., Liu, L., Yu, P.S., 2007. ASAP: an adaptive sampling approach to data collection in sensor networks. IEEE Trans. Parall. Distr. Syst., 18(12):1766–1783. [doi:10.1109/TPDS.2007.1110]

    Article  Google Scholar 

  15. Gupta, P., Kumar, P.R., 2000. The capacity of wireless networks. IEEE Trans. Inf. Theory, 46(2):388–404. [doi:10.1109/18.825799]

    MATH  Article  MathSciNet  Google Scholar 

  16. Heinzelman, W.B., Chandrakasan, A.P., Balakrishnan, H., 2002. IEEE Trans. Wirel. Commun., 1(4):660–670. [doi:10.1109/TWC.2002.804190]

    Article  Google Scholar 

  17. Hull, B., Jamieson, K., Balakrishnan, H., 2004. Mitigating Congestion in Wireless Sensor Networks. Proc. 2nd Int. Conf. on Embedded Networked Sensor Systems, p.134–147. [doi:10.1145/1031495.1031512]

  18. Jain, K., Padhye, J., Padmanabhan, V.N., Qiu, L.L., 2003. Impact of Interference on Multi-Hop Wireless Network Performance. Proc. 9th Annual Int. Conf. on Mobile Computing and Networking, p.66–80. [doi:10.1145/938985.938993]

  19. Kang, J., Zhang, Y.Y., Nath, B., 2007. TARA: topology-aware resource adaption to alleviate congestion in sensor networks. IEEE Trans. Parall. Distr. Syst., 18(7):919–931. [doi:10.1109/TPDS.2007.1030]

    Article  Google Scholar 

  20. Kumar, R., Crepaldi, R., Rowaihy, H., Harris, A.F., Cao, G.H., Zorzi, M., Porta, L.T., 2008. Mitigating performance degradation in congested sensor networks. IEEE Trans. Mob. Comput., 7(6):682–697. [doi:10.1109/TMC.2008.20]

    Article  Google Scholar 

  21. Liu, C., Wu, K., Pei, J., 2007. An energy-efficient data collection framework for wireless sensor networks by exploiting spatiotemporal correlation. IEEE Trans. Parall. Distr. Syst., 18(7):1010–1023. [doi:10.1109/TPDS.2007.1046]

    Article  Google Scholar 

  22. Misra, S., Tiwari, V., Obaidat, M., 2009. LACAS: learning automata-based congestion avoidance scheme for healthcare wireless sensor networks. IEEE J. Sel. Areas Commun., 27(4):466–479. [doi:10.1109/JSAC.2009.090510]

    Article  Google Scholar 

  23. Popa, L., Raiciu, C., Stoica, I., Rosenblum, D., 2006. Reducing Congestion Effects in Wireless Networks by Multipath Routing. Proc. IEEE Int. Conf. on Network Protocols, p.96–105. [doi:10.1109/ICNP.2006.320202]

  24. Teo, J.Y., Ha, Y.J., Tham, C.K., 2008. Interference-minimized multipath routing with congestion control in wireless sensor network for high-rate streaming. IEEE Trans. Mob. Comput., 7(9):1124–1137. [doi:10.1109/TMC.2008.24]

    Article  Google Scholar 

  25. Vuran, M.C., Akyildiz, I.F., 2006. Spatial correlation-based collaborative medium access control in wireless sensor networks. IEEE Trans. Network., 14(2):316–329. [doi:10.1109/TENT.2006.872544]

    Article  Google Scholar 

  26. Wan, C.Y., Eisenman, S.B., Campbell, A.T., 2003. CODA: Congestion Detection and Avoidance in Sensor Networks. Proc. 1st Int. Conf. on Embedded Networked Sensor Systems, p.266–279. [doi:10.1145/958491.958523]

  27. Wan, C.Y., Eisenman, S.B., Campbell, A.T., Crowcroft, J., 2005. Siphon: Overload Traffic Management Using Multi-Radio Virtual Sinks in Sensor Networks. Proc. 3rd Int. Conf. on Embedded Networked Sensor Systems, p.116–129. [doi:10.1145/1098918.1098931]

  28. Yu, Y.Q., Giannakis, G.B., 2009. Cross-layer congestion and contention control for wireless ad hoc networks. IEEE Trans. Wirel. Commun., 1(7):37–42. [doi:10.1109/TWC.2008.060514]

    Google Scholar 

  29. Zhao, M., Chen, Z.G., Zhang, L., Ge, Z.H., 2007. HS-Sift: hybrid spatial correlation-based medium access control for event-driven sensor networks. IET Commun., 1(6):1126–1132. [doi:10.1049/iet-com:20060128]

    Article  Google Scholar 

  30. Zhang, Q., Yang, X.L., Zhou, Y.M., Wang, L.R., Guo, X.S., 2007. A wireless solution for greenhouse monitoring and control system based on ZigBee technology. J Zhejiang Univ. Sci A, 8(10):1584–1587. [doi:10.1631/jzus.2007.A1584]

    Article  Google Scholar 

  31. Zhou, Y.F., Lyu, R.M., Liu, J.C., Wang, H., 2005. PORT: A Price-Oriented Reliable Transport Protocol for Wireless Sensor Networks. Proc. 16th IEEE Int. Symp. on Software Reliability Engineering, p.117–126. [doi:10.1109/ISSRE.2005.32]

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Wei-wei Fang.

Additional information

Project supported by the National Natural Science Foundation of China (Nos. 60673180, 90412011 and 90612004), the International Science and Technology Cooperative Program of China (No. 2006DFA11080), the Research Program of Federal Ministry of Education and Research of Germany (No. 01BU0680), and the Lion Project of Science Foundation of Ireland to Lei Shu (No. SFI/08/CE/I1380)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Fang, W., Chen, J., Shu, L. et al. Congestion avoidance, detection and alleviation in wireless sensor networks. J. Zhejiang Univ. - Sci. C 11, 63 (2010). https://doi.org/10.1631/jzus.C0910204

Download citation

Key words

  • Wireless sensor network (WSN)
  • Congestion control
  • Correlation
  • Traffic multiplexing
  • Rate regulation

CLC number

  • TP393