Skip to main content

DTR-Filter: An Efficient Transmission Scheme for Real-Time Monitoring in Wireless Bulky Sensor Networks

  • Conference paper
Convergence and Hybrid Information Technology (ICHIT 2011)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6935))

Included in the following conference series:

  • 1856 Accesses

Abstract

Wireless sensor networks basically assume the low duty-cycle data to be generated. But as the area of applications become wide, bulky sensor data might be generated and need to be transmitted. The sensor devices have limited resources in CPU, battery and memory capacity. As well as data transmission and reception are major factor of energy consumption in sensor nodes, network bandwidth may be easily overrun with bulk data transmission. So the reduction of data transmission is very important in bulky sensor data transmission. We proposed a data filtering algorithm, DTR-filter, to suppress the trivial value changes in transmission while encouraging the transmission of important event values. Our DTR-filter algorithm adaptively controls the filtering criteria. DTR-filter showed 53% of average reduction in data transmission while having 86% of correctness with original unfiltered data.

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 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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. Heinzelamn, W., Chandrakasan, A., Balarkrishnan, H.: Energy efficient communication protocol for wireless microsensor networks. In: The Proceedings of HICSS 2000 (January 2000)

    Google Scholar 

  2. Vlajic, N., Xia, D.: Wireless Sensor Networks: To Cluster or Not To Cluster. In: Proc. of the 2006 International Symposium on a World of Wireless, Mobile and Multimedia Networks. IEEE Computer Society, York University, Toronto, Canada (2006)

    Google Scholar 

  3. Jiao, W., Cheng, L., Chen, M., Chen, C., Ma, J.: Efficient Data Delivery inWireless Sensor Networks with Ubiquitous Mobile Data Collectors. In: 2010 IEEE/IFIP International Conference on Embedded and Ubiquitous Computing (2010)

    Google Scholar 

  4. Ghaffariyan, P.: An Effective Data Aggregation Mechanism for Wireless Sensor Networks. In: 2010 6th International Conference on Wireless Communications Networking and Mobile Computing, WiCOM (2010)

    Google Scholar 

  5. Bhattacherjee, S., Narang, A., Garg, V.K.: High throughput data redundancy removal algorithm with scalable performance. In: HiPEAC 2011, Heraklion, pp. 87–96 (2011)

    Google Scholar 

  6. Broder, A., Mitzenmacher, M.: Network Applications of Bloom Filters: A Survey. Internet Mathematics 1(4), 485–509 (1970)

    Article  MathSciNet  MATH  Google Scholar 

  7. Fan, L., Cao, P., Almeida, J., Broder, Z.: Summary cache: a scalable wide area web cache sharing protocol. IEEE/ACM Transaction on Networking, 281–293 (2000)

    Google Scholar 

  8. Dong, W., Chen, C., Bu, J., Liu, Y.: Performance of Bulk Data Dissemination in Wireless Sensor Networks. In: Krishnamachari, B., Suri, S., Heinzelman, W., Mitra, U. (eds.) DCOSS 2009. LNCS, vol. 5516. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  9. Lee, K., Ahn, S., Hong, B., Kim, K.: Efficient Query Processing on Bulk Data of Sensor and Location. In: 2010 Fourth International Conference on Sensor Technologies and Applications, SENSORCOMM (2010)

    Google Scholar 

  10. Huang, L., Setia, S.: CORD: Energy-Efficient Reliable Bulk Data Dissemination in Sensor Networks. In: INFOCOM 2008 The 27th Conference on Computer Communications. IEEE, Los Alamitos (2008)

    Google Scholar 

  11. Jain, A., Chang, E.Y.: Adaptive sampling for sensor networks. In: Proceeedings of the 1st International Workshop on Data Management for Sensor Networks, DMSN 2004 (2004)

    Google Scholar 

  12. Kalman, R.E.: A new approach to linear filtering and prediction problems. Transactions of the ASME–Journal of Basic Engineering 82(Series D), 35–45 (1960)

    Article  Google Scholar 

  13. Marbini, A.D., Sacks, L.E.: Adaptive sampling mechanisms in sensor networks (2003)

    Google Scholar 

  14. XML, http://www.w3schools.com/xml/default.asp

  15. IEEE Standard for a Smart Transducer Interface for Sensors and Actuators—Wireless Communication Protocols and Transducer Electronic Data Sheet (TEDS) Formats, IEEE standard (2007)

    Google Scholar 

  16. Jfreechart, http://www.jfree.org/jfreechart/

  17. Derin, O.: A Tutorial on Reporting in JAVA using JasperReports, iReport and JfreeChart (2005)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Qian, Y., Kang, J., Kim, J., Min, J., Kwon, Y. (2011). DTR-Filter: An Efficient Transmission Scheme for Real-Time Monitoring in Wireless Bulky Sensor Networks. In: Lee, G., Howard, D., Ślęzak, D. (eds) Convergence and Hybrid Information Technology. ICHIT 2011. Lecture Notes in Computer Science, vol 6935. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24082-9_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-24082-9_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24081-2

  • Online ISBN: 978-3-642-24082-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics