KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
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Analysis of Optimized Aggregation Timing in Wireless Sensor Networks

  • Lee, Dong-Wook (Graduate School of Information and Communication, Ajou University) ;
  • Kim, Jai-Hoon (Graduate School of Information and Communication, Ajou University)
  • Published : 2009.04.25
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Abstract

In a wireless sensor network(WSN) each sensor node deals with numerous sensing data elements. For the sake of energy efficiency and network lifetime, sensing data must be handled effectively. A technique used for this is data aggregation. Sending/receiving data involves numerous steps such as MAC layer control packet handshakes and route path setup, and these steps consume energy. Because these steps are involved in all data communication, the total cost increases are related to the counts of data sent/received. Therefore, many studies have proposed sending combined data, which is known as data aggregation. Very effective methods to aggregate sensing data have been suggested, but there is no means of deciding how long the sensor node should wait for aggregation. This is a very important issue, because the wait time affects the total communication cost and data reliability. There are two types of data aggregation; the data counting method and the time waiting method. However, each has weaknesses in terms of the delay. A hybrid method can be adopted to alleviate these problems. But, it cannot provide an optimal point of aggregation. In this paper, we suggest a stochastic-based data aggregation scheme, which provides the cost(in terms of communication and delay) optimal aggregation point. We present numerical analysis and results.

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References

  1. I. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “A Survey on Sensor Networks,” IEEE Communication Magazine, pp.6-28, Aug. 2002.
  2. A. Mainwaring, J. Polastre, R. Szewczyk, D. Culler, and J. Anderson, “Wireless Sensor Networks for Habitat Monitoring,” in Proceeding of WSNA 2002, Atlanta, Georgia, USA, pp.88-97, Sep. 2002.
  3. A. Ailamaki, C. Faloutos, P.S. Fischbeck, M.J. Small and J.V. Briensen, “An environmental sensor network to determine drinking water quality and security,” in SPECIAL ISSUE: Special section on sensor network technology and sensor data management, SIGMOD, vol.32, no.4, pp.47-52, Dec. 2003.
  4. A. LaMarca, W. Brunnete, D. Koizumi, M. Lease, S.B. Sigurdsson, K. Sikorski, D. Fox and G. Borriello, “Making sensor network practical with robots,” in Proceedings of the First International Conference on Pervasive Computing, LNCS, vol.2414, pp.152-166, 2002.
  5. W. Ye, J. Heidemann and D. Estrin, “An energy efficient MAC protocol for wireless sensor networks,” in Proc. IEEE INFOCOM 2002, vol.3, pp.1567-1576, June 2002.
  6. B. Krishnamachari, D. Estrin and S.B. Wicker, “The impact of data aggregation in wireless sensor networks,” in ICDCSW '02: Proceedings of the 22nd International Conference on Distributed Computing Systems, pp.575-578, 2002.
  7. M. Busse, T. Haenselmann and W. Effelsberg, “TECA: A Topology and Energy Control Algorithm for Wireless Sensor Networks,” in ACM Proceedings of Modeling analysis and Simulation of Wireless and Mobile Systems (MSWiM), Oct. 2006.
  8. Y. Chen and S.H. Son, “A fault tolerant topology control in wireless sensor networks,” in ACS/IEEE International Conference on Computer Systems and Applications (AICCSA), Jan. 2005.
  9. R. Ghosh and S. Basagni, “Napping backbones: energy efficient topology control for wireless sensor networks,” in IEEE Radio and Wireless Symposium (RWS), Jan. 2006.
  10. W.P. Chen, J.C. Hou and L. Sha, “Dynamic clustering for acoustic target tracking in wireless sensor networks,” in IEEE Transactions on Mobile Computing, vol.3, no.3, pp.258-271, July 2004. https://doi.org/10.1109/TMC.2004.22
  11. J.Y. Cheng, S.Ruan, R.Cheng and T.Hsu, “PADCP: Power-Aware Dynamic Clustering Protocol for Wireless Sensor Network,” in IFIP International Conference on Wireless and Optical Communications Networks (WOCN), Apr. 2006.
  12. Y. Yang, X. Wang, S. Zhu and G. Cao, “SDAP: A Secure Hop-by-Hop Data Aggregation Protocol for Sensor Networks,” ACM Transactions on Information and System Security, vol.11, no.4, pp.1-43, July 2008.
  13. F. Hu and C. May, “Timing Control During Data Aggregation Operations of Distributed Sensor Networks: Trade-off Between Query Accuracy and Response Delay,” Information Technology Journal, vol.5, no.5, pp.759-778, 2006. https://doi.org/10.3923/itj.2006.759.778
  14. H. Li, H. Yu, B. Yang and A. Liu, “Timing control for delay-constrained data aggregation in wireless sensor networks,” International Journal of Communication Systems, vol.20, pp.875-887, 2007. https://doi.org/10.1002/dac.849
  15. S. J. Park, “Performance Analysis of Data Aggregation Schemes for Wireless Sensor Networks Static-cluster aggregation and Dynamic-cluster aggregation Section,” A dissertation for Doctoral in North Carolina State University, 2006.
  16. E. Fasolo, M. Rossi, J. Widmer and M.Zorzi, “In-network Aggregation Techniques for Wireless Sensor Networks: A Survey,” IEEE Wireless Communications, vol.14, no.2, pp.70-87, Apr. 2007.
  17. Crossbow MICA2 mote Data Sheets, http://www.xbow.com

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