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Packet Length Adaptation for Energy-Proportional Routing in Clustered Sensor Networks

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Emerging Directions in Embedded and Ubiquitous Computing (EUC 2006)
Packet Length Adaptation for Energy-Proportional Routing in Clustered Sensor Networks
  • Chao-Lieh Chen26,
  • Chia-Yu Yu27,
  • Chien-Chung Su27,
  • Mong-Fong Horng28 &
  • …
  • Yau-Hwang Kuo27 

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4097))

Included in the following conference series:

  • International Conference on Embedded and Ubiquitous Computing
  • 1973 Accesses

  • 3 Citations

Abstract

We study the maximization of throughput and energy utilization in noisy wireless channels by adjusting packet length adaptively to network instant statistics. The optimal packet length adaptation (PLA) for throughput and energy utilization in wireless networks with and without re-transmission is respectively derived and developed. As more noises introducing more energy consumptions, the noises are equivalently regarded as lengthening of transmission distances. Therefore, an equivalent distance model of noisy channels is developed for more accurate estimation of the dissipated proportion in the residual energy such that further improvement of energy utilization and throughput is obtained. We integrate the PLA with the energy-proportional routing (EPR) algorithm for best balance of energy load. Therefore, performance metrics such as lifetime extension, throughput, and energy utilization are maximized even the distribution of channel noise is so un-predictable. Since the equivalent distance is dynamic, we believe that it is useful for network topology re-organization and will be useful in the future work of mobile ad-hoc networks.

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References

  1. Heinzelman, W., Chandrakasan, A., Balakrishnan, H.: An Application-Specific Protocol Architecture for Wireless Microsensor Networks. IEEE Transactions on Wireless Communications 1(4), 660–670 (2002)

    Article  Google Scholar 

  2. Lindsey, S., Raghavendra, C., Sivalingam, K.M.: Data Gathering Algorithms in Sensor Networks Using Energy Metrics. IEEE Transactions on Parallel and Distributed Systems 13(9), 924–935 (2002)

    Article  Google Scholar 

  3. Lindsey, S., Raghavendra, C.: PEGASIS: Power-Efficient Gathering in Sensor Information Systems. In: IEEE Aerospace Conference Proceedings, vol. 3, pp. 1125–1130 (2002)

    Google Scholar 

  4. Younis, O., Fahmy, S.: Distributed Clustering in Ad-hoc Sensor Networks: A Hybrid, Energy-Efficient Approach. IEEE Transactions on Mobile Computing 3(4), 366–379 (2004)

    Article  Google Scholar 

  5. Younis, O., Fahmy, S.: Distributed Clustering in Ad-Hoc Sensor Networks: A Hybrid, Energy-Efficient Approach. In: Proceedings of IEEE INFOCOM (2004)

    Google Scholar 

  6. Muruganathan, S.D., Ma, D.C.F., Bhasin, R.I., Fapojuwo, A.O.: A Centralized Energy-Efficient Routing Protocol for Wireless Sensor Networks. IEEE Radio Communications 43(3), S8–S13 (2005)

    Article  Google Scholar 

  7. Wang, X., Yin, J., Agrawal, D.P.: Effects of Contention Window and Packet Size on the Energy Efficiency of Wireless Local Area Network. In: Proceedings of 2005 IEEE Wireless Communications and Networking Conference, vol. 1, pp. 94–99 (2005)

    Google Scholar 

  8. Bischl, H., Lutz, E.: Packet error rate in the non-interleaved Rayleigh channel. IEEE Transactions on Communications 43, 1375–1382 (1995)

    Article  Google Scholar 

  9. Reggiannini, R.: A lower performance bound for phase estimation over slowly-fading Ricean channels. In: Global Telecommunications Conference, vol. 3, pp. 2012–2016 (1995)

    Google Scholar 

  10. Muruganathan, S.D., Ma, D.C.F., Bhasin, R.I., Fapojuwo, A.O.: A Centralized Energy-Efficient Routing Protocol for Wireless Sensor Networks. IEEE Radio Communications, S8–S13 (2005)

    Google Scholar 

  11. Chen, C.-L., Lee, K.-R., et al.: An Energy-proportional Routing Algorithm for Lifetime Extension of Clustering-based Wireless Sensor Networks. In: Workshop on Wireless, Ad Hoc, and Sensor Networks, Taiwan (2005), http://acnlab.csie.ncu.edu.tw/WASN

  12. Chen, C.-L., Lee, K.-R., et al.: An Energy-proportional Routing Algorithm for Lifetime Extension of Clustering-based Wireless Sensor Networks. Journal of Pervasive Computing and Communications 2 (to appear, 2006)

    Google Scholar 

  13. Cover, T.M., Thomas, J.A.: Elements of Information Theory (1991)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electronics Engineering, Kun-Shan University, Yung-Kang, Tainan County, Taiwan, R.O.C.

    Chao-Lieh Chen

  2. Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan, R.O.C.

    Chia-Yu Yu, Chien-Chung Su & Yau-Hwang Kuo

  3. Department of Computer Science and Information Engineering, Shu-Te University, Kao-Hsiung, Taiwan, R.O.C.

    Mong-Fong Horng

Authors
  1. Chao-Lieh Chen
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  2. Chia-Yu Yu
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  3. Chien-Chung Su
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  4. Mong-Fong Horng
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  5. Yau-Hwang Kuo
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Editor information

Editors and Affiliations

  1. HCNR Centre for Bioinformatics Harvard Medical School, 02215, Boston, MA, USA

    Xiaobo Zhou

  2. Department of Computer Science, University of Pennsylvania, 19104-6389, Philadelphia, PA, USA

    Oleg Sokolsky

  3. School of Computer Science, University of Hertfordshire, College Lane, Hatfield, 10 9AB, Hertfordshire, AL, UK

    Lu Yan

  4. Networking Technology Laboratory, Samsung Advanced Institute of Technology,  

    Eun-Sun Jung

  5. Department of Computing, The Hong Kong polytechnic University, Hong Kong

    Zili Shao

  6. Centre for Computer and Information Security Research School of Computer Science and Software Engineering, University of Wollongong, Australia

    Yi Mu

  7. Dept. of Computer Science, Howon Univ., Korea

    Dong Chun Lee

  8. Empas Corporation, Republic of Korea

    Dae Young Kim

  9. Dept. of Computer Engineering, Wonkwang University, 344-2 Shinyong-Dong, Iksan, 570-749, Jeonbuk,, S. Korea

    Young-Sik Jeong

  10. Department of Electrical & Computer Engineering, Wayne State University, 5050 Anthony Wayne Drive, Detroit, 48202, MI, USA

    Cheng-Zhong Xu

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© 2006 Springer-Verlag Berlin Heidelberg

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Chen, CL., Yu, CY., Su, CC., Horng, MF., Kuo, YH. (2006). Packet Length Adaptation for Energy-Proportional Routing in Clustered Sensor Networks. In: Zhou, X., et al. Emerging Directions in Embedded and Ubiquitous Computing. EUC 2006. Lecture Notes in Computer Science, vol 4097. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11807964_4

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  • DOI: https://doi.org/10.1007/11807964_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-36850-2

  • Online ISBN: 978-3-540-36851-9

  • eBook Packages: Computer ScienceComputer Science (R0)Springer Nature Proceedings Computer Science

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Keywords

  • Sensor Network
  • Sensor Node
  • Wireless Sensor Network
  • Cluster Head
  • Energy Utilization

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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