Skip to main content

Approaching the Optimal Schedule for Data Aggregation in Wireless Sensor Networks

  • Conference paper
Wireless Algorithms, Systems, and Applications (WASA 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6221))

Abstract

Due to the large-scale ad hoc deployments and wireless interference, data aggregation is a fundamental but time consuming task in wireless sensor networks. This paper focuses on the latency of data aggregation. Previously, it has been proved that the problem of minimizing the latency of data aggregation is NP-hard [1]. Using maximum independent set and first fit algorithms, in this study we design a scheduling algorithm, Peony-tree-based Data Aggregation (PDA), which has a latency bound of 15R + Δ− 15, where R is the network radius (measured in hops) and Δ is the maximum node degree. We theoretically analyze the performance of PDA based on different network models, and further evaluate it through extensive simulations. Both the analytical and simulation results demonstrate the advantages of PDA over the state-of-art algorithm in [2], which has a latency bound of 23R + Δ− 18.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Xujin, C., Xiaodong, H., Jianming, Z.: Minimum data aggregation time problem in wireless sensor networks. In: 1st International Conference on Mobile Ad-hoc and Sensor Networks, pp. 133–142. IEEE Press, Wuhan (December 2005)

    Google Scholar 

  2. Scott, C.-H.H., Peng-Jun, W., Chinh, T.V., et al.: Nearly constant approximation for data aggregation scheduling in wireless sensor networks. In: Proceedings of INFOCOM, pp. 366–372. IEEE Press, Anchorage (May 2007)

    Google Scholar 

  3. Ian, F.A., Weilian, S., Yogesh, S., Erdal, C.: Wireless sensor networks: a survey. Computer Networks 38(4), 393–422 (2002)

    Article  Google Scholar 

  4. Mo, L., Yunhao, L.: Underground structure monitoring with wireless sensor networks. In: Proceedings of ACM/IEEE IPSN, pp. 69–78. ACM Press, Cambridge (April 2007)

    Google Scholar 

  5. Robert, S., Alan, M.M., Joseph, P., et al.: An analysis of a large scale habitat monitoring application. In: Proceedings of ACM SenSys, pp. 214–226. ACM Press, Baltimore (November 2004)

    Google Scholar 

  6. Mo, L., Yunhao, L.: Iso-map: Energy-efficient contour mapping in wireless sensor networks. IEEE Transactions on Knowledge and Data Engineering (TKDE) 22(5), 699–710 (2010)

    Article  Google Scholar 

  7. Mo, L., Yunhao, L., Lei, C.: Non-threshold based event detection for 3d environment monitoring in sensor networks. IEEE Transactions on Knowledge and Data Engineering (TKDE) 20(12), 1699–1711 (2008)

    Article  Google Scholar 

  8. Kebin, L., Mo, L., Yunhao, L., et al.: Passive diagnosis for wireless sensor networks. In: Proceedings of ACM SenSys, pp. 113–126. ACM Press, Raleigh (November 2008)

    Google Scholar 

  9. Lufeng, M., Yuan, H., Yunhao, L., et al.: Canopy closure estimates with greenorbs: Sustainable sensing in the forest. In: Proceedings of ACM Sensys, pp. 99–112. ACM Press, Berkeley (November 2008)

    Google Scholar 

  10. Alexander, K., Dariusz, R.K.: Fast distributed algorithm for convergecast in ad hoc geometric radio networks. J. Parallel Distrib. Comput. 66(4), 578–585 (2006)

    Article  MATH  Google Scholar 

  11. Wegner, G.: Über endliche kreispackungen in der ebene. Studia Scientiarium Mathematicarium Hungarica 21, 1–28 (1986)

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Wang, P., He, Y., Huang, L. (2010). Approaching the Optimal Schedule for Data Aggregation in Wireless Sensor Networks. In: Pandurangan, G., Anil Kumar, V.S., Ming, G., Liu, Y., Li, Y. (eds) Wireless Algorithms, Systems, and Applications. WASA 2010. Lecture Notes in Computer Science, vol 6221. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14654-1_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-14654-1_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14653-4

  • Online ISBN: 978-3-642-14654-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics