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Proceedings of the 2022 Seventh International Conference on Research in Intelligent and Computing in Engineering

Annals of Computer Science and Information Systems, Volume 33

CRSDF: Improved Network Lifespan through Chain-routing Scheme and Data Fusion in Wireless Sensor Network

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DOI: http://dx.doi.org/10.15439/2022R16

Citation: Proceedings of the 2022 Seventh International Conference on Research in Intelligent and Computing in Engineering, Vu Dinh Khoa, Shivani Agarwal, Gloria Jeanette Rincon Aponte, Nguyen Thi Hong Nga, Vijender Kumar Solanki, Ewa Ziemba (eds). ACSIS, Vol. 33, pages 219–225 ()

Full text

Abstract. How to use efficient energy in wireless sensor networks (WSN) is one of the major challenges due to limited energy batteries and computation capacity. Therefore, in this paper, we propose combining a chain-base routing scheme and data fusion sensor information (CRSDF for short). CRSDF contains two major works: Firstly, the chain-based routing method is applied to connect sensor nodes into a chain in which each node transmits only with the nearest neighbor using the remaining energy and distance of nodes as standard parameters to determine which node will be selected the chain leader, secondly, we fuse and compress one or more data packets to generate a result packet with small size base on the Slepian-Wolf and Dempster-Shafer theory. The simulation results exhibit that the energy efficiency of our proposed protocol can be improved by 40\%, 20\%, and 15\% compared to low-energy adaptive clustering hierarchy (LEACH), power-efficient gathering in sensor information system (PEGASIS), and an improved energy-efficient PEGASIS-Based protocol, respectively.

References

  1. Yang, X., Pei, X., Chen, G., Li, T., Wang, M., & Wang, C. (2019). A Strongly Unforgeable Certificateless Signature Scheme and Its Application in IoT Environments. Sensors, 19(12), 1 – 27.
  2. S. Lindsey and C. S. Raghavendra, “Pegasis: Power-efficient gathering in sensor information system,” in IEEE Aerospace Conference Proceedings, March 2002, pp. 1125 – 1130.
  3. L. Zi, W. Chen, X. Liu, and X. Chen, “A novel chain-based routing protocol, branchain, in wireless sensor networks,” International Journal of Embedded Systems, vol. 11, no. 3, pp. 259–268, 2019.
  4. M. Malleswari, B. A. Krishna, N. Madhuri, and M. K. Chowdary, “Implementation of modified huffman coding in wireless sensor networks,” International Journal of Computer Applications, vol. 177, no. 1, pp. 14–17, 2017.
  5. K. Sayood, Lossless Compression Handbook. California, USA: Academic Press, 2003.
  6. D. Slepian and J. K. Wolf, “Noiselesscoding of correlated information source,” IEEE Transactions on Information Theory, vol. 19, no. 4, pp. 471–480, 1973.
  7. P. Kumar and V. Gupta, “Data compression using distributed source coding in wireless sensor network,” International Journal of Electronics Communication and Computer Technology, vol. 2, no. 1, 2011.
  8. K.-C. Lan and M.-Z. Wei, “A compressibility-based clustering algorithm for hierarchical compressive data gathering,” IEEE Sensors Journal, vol. 17, no. 8, pp. 2550–2562, 2017.
  9. I. Ullah, J. Youn, and Y.-H. Han, “Multisensor data fusion based on modified belief entropy in dempster–shafer theory for smart environment,” IEEE Access, vol. 9, pp. 37 813–37 822, 2021.
  10. W. B. Heinzelman, A. P. Chandrakasan, and H. Balakrishnan, “An Application-Specific Protocol Architecture for Wireless Microsensor Networks,” IEEE Transactions on wireless communication, vol. 1, no. 4, pp. 660–670, 2002.
  11. F. Sen, Q. Bing, and T. Liangrui, “An Improved Energy-Efficient PEGASIS-Based Protocol in Wireless Sensor Networks,” in Eighth International Conference on Fuzzy Systems and Knowledge Discovery. Shanghai, China, July 2011, pp. 2230–2233.
  12. H. Wu, H. Zhu, L. Zhang, and Y. Song, “Energy efficient chain based routing protocol for orchard wireless sensor network,” Journal of Electrical Engineering & Technology, vol. 14, p. 2137–2146, 2019.
  13. S. S, S. E, and D. D, “Enhanced energy efficient routing for wireless sensor network using extended power efficient gathering in sensor information systems (e-pegasis) protocol,” Procedia Computer Science, vol. 194, p. 89–101, 2021, the 18th International Learning & Technology Conference.
  14. H. Duong-Viet and V. Nguyen-Dinh, “Df-swin- sliding windows for multi-sensor data fusion in wireless sensor networks,” in The 9th International Conference on Knowledge and Systems Engineering (KSE). Hue, Vietnam, October 2017, pp. 54–59.
  15. C. M. Sadler and M. Martonosi, “Data compression algorithms for energy-constrained devices in delay tolerant networks,” in Proceedings of the 4th international conference on Embedded networked sensor systems. Boulder, Colorado,USA, November 2006, pp. 265–278.
  16. Z. Xiong, A. D. Liveris, and S. Cheng, “Distributed source coding for sensor networks,” IEEE Signal Processing Magazine, vol. 21, no. 5, pp. 80 – 94, 2004.
  17. G. Shafer, A Mathematical Theory of Evidence. Princeton University Press, 1976.
  18. E. D. C. Bezerra, A. S. Teles, L. R. Coutinho, and F. J. da Silva e Silva, “Dempster–shafer theory for modeling and treating uncertainty in iot applications based on complex event processing,” Sensors, vol. 21, no. 5, pp. 1–26, 2021.
  19. Tan, N, D.,& Viet, N, D. "SCBC: Sector-Chain Based Clustering Routing Protocol for Energy Efficiency in Heterogeneous Wireless Sensor Network", Advanced Technologies for Communications (ATC), Ho Chi Minh, Vietnam, 2015, pp. 314-319.
  20. Van-Hau, N, Nam, V. H., Linh, D, M., and Quy, V. K., (2021), An improved agent-based AODV routing protocol for MANET, EAI Endorsed Transactions on Industrial Networks and Intelligent Systems, 8(27), 2021.
  21. Tan, N, D., Quy, K, V., Hung, P, N., & Vinh, L, V. (2021). Sector Tree-Based Clustering For Energy Efficient Routing Protocol in Heterogeneous Wireless Sensor Network, International Journal of Computer Networks & Communications (IJCNC), 13(5), 57-74.
  22. W. Heinzelman, “MIT uAMPS LEACH ns Extensions,” https://blog.katastros.com/a?ID=01700-10dfaae3-e3c2-4f2f-8235- 608c3010d995 (accessed: Feb 29, 2022), 2004.
  23. VINT Project, “The network simulator - NS2,” http://www.isi.edu/nsnam/ns (accessed: Feb 2, 20212, 1997.