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Prolonging the lifetime of wireless sensor networks by utilizing feedback control

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Abstract

A new algorithm aiming to prolong the lifetime of wireless sensor networks (WSNs) is proposed to balance energy depletion. Using a feedback control combined with a discrete nonlinear programming method to adjust the transmission radii of sensor nodes located in different locations, makes network load redistribution possible and balances energy consumption, further prolongs the lifetime of the entire network. A data distribution model which specific to WSNs with sensor nodes that can adjust transmission radii is proposed to analyze the load spread of the network. This model contributes to predicting and analyzing energy consumption balance effectively. Compared with two other algorithms, dynamic transmission range adjustment and SP, respectively, the experimental results show that the proposed algorithm can lengthen the lifetime of WSNs by up to 22.7 and 27.2 %.

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References

  1. Ghataoura, D. S., Mitchell, J. E., & Matich, G. E. (2011). Networking and application interface technology for wireless sensor network surveillance and monitoring. IEEE Communication Magazine, 49(10), 90–97.

    Article  Google Scholar 

  2. Zhuiykov, S. (2012). Solid-state sensors monitoring parameters of water quality for the next generation of wireless sensor networks. Sensors and Actuators B: Chemical, 161(1), 1–20.

    Article  Google Scholar 

  3. Li, M., & Liu, Y. (2007). Underground structure monitoring with wireless sensor networks. In Proceedings of sixth IEEE/ACM international conference information processing in sensor networks (IPSN’07) (pp. 69–78).

  4. Placzek, B. (2012). Selective data collection in vehicular networks for traffic control applications. Transportation Research Part C: Emerging Technologies, 23, 14–28.

    Article  Google Scholar 

  5. Li, J., & Mohapatra, P. (2005). An analytical model for the energy hole problem in many-to-one sensor networks. In IEEE VTS vehicular technology conference proceedings (pp. 2721–2725).

  6. Li, Q.-Q., Gong, H., Liu, M., Yang, M., & Zheng, J. (2011). On prolonging network lifetime through load-similar node deployment in wireless sensor networks. Sensors, 11(4), 3527–3544.

    Article  Google Scholar 

  7. Olariu, S., & Stojmenovic, I. (2006). Design guidelines for maximizing lifetime and avoiding energy holes in sensor networks with uniform distribution and uniform reporting. In Proceedings of 25th IEEE INFOCOM conference (pp. 2505–2516).

  8. Bagaa, M., Challal, Y., Ouadjaout, A., Lasla, N., & Badachea, N. (2012). Efficient data aggregation with in-network integrity control for WSN. Journal of Parallel and Distributed Computing, 72, 1157–1170.

    Article  Google Scholar 

  9. Larios, D. F., Barbancho, J., Rodríguez, G., Sevillano, J. L., Molina, F. J., & León, C. (2012). Energy efficient wireless sensor network communications based on computational intelligent data fusion for environmental monitoring. IET Communications, 6(14), 2189–2197.

    Article  Google Scholar 

  10. Zeydan, E., Kivanc, D., Comaniciu, C., & Tureli, U. (2012). Energy-efficient routing for correlated data in wireless sensor networks. Ad Hoc Networks, 10, 962–975.

    Article  Google Scholar 

  11. Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless microsensor networks. In Proceedings of 33rd Hawaii international conference on system sciences, USA (Vol. 8, p. 8020).

  12. Lindsey, S., Raghavendra C. S. (2002). PEGASIS: Power-efficient gathering in sensor information systems. In Proceedings of the IEEE aerospace conference, Montana, USA (Vol. 3, pp. 1125–1130).

  13. Sinha, K., Sinha, B. P., & Datta, D. (2010). CNS: A new energy efficient transmission scheme for wireless sensor networks. Wireless Network, 16(8), 2087–2104.

    Article  Google Scholar 

  14. Mitton, N., Razafindralambo, T., Simplot-Ryl, D., & Stojmenovic, I. (2012). Towards a hybrid energy efficient multi-tree-based optimized routing protocol for wireless networks. Sensors, 12(12), 17295–17319.

    Article  Google Scholar 

  15. Cheng, S.-T., & Chang, T.-Y. (2012). An adaptive learning scheme for load balancing with zone partition in multi-sink wireless sensor network. Expert Systems with Applications, 39, 9427–9434.

    Article  MathSciNet  Google Scholar 

  16. Chang, C.-Y., Lin, C.-Y., & Kuo, C.-H. (2012). EBDC: An energy-balanced data collection mechanism using a mobile data collector in WSNs. Sensors, 12(5), 5850–5871.

    Article  Google Scholar 

  17. Keskın, M. E., Altinel, I. K., Aras, N., & Ersoy, C. (2011). Lifetime maximization in wireless sensor networks using a mobile sink with nonzero traveling time. Computer Journal, 54(12), 1987–1999.

    Article  Google Scholar 

  18. Zhiewen, Z., Chen, Z. G., & Liu, A. F. (2010). Energy-hole avoidance for WSN based on adjust transmission power. Chinese Journal of Computers, 33(1), 12–22.

    Article  Google Scholar 

  19. Wu, X., Chen, G., & Das, S. K. (2008). Avoiding energy holes in wireless sensor networks with nonuniform node distribution. IEEE Transactions on Parallel Distributed Systems, 19(5), 710–720.

    Article  Google Scholar 

  20. Bouabdallah, F., Bouabdallah, N., & Boutaba, R. (2009). On balancing energy consumption in WSNs. IEEE Transactions on Vehicular Technology, 58(6), 2909–2924.

    Article  Google Scholar 

  21. Ren, F., Zhang, J., He, T., Lin, C., & Ren, S. K. (2011). EBRP: Energy-balanced routing protocol for data gathering in WSNs. IEEE Transactions on Parallel Distributed Systems, 22(12), 2108–2125.

    Article  Google Scholar 

  22. Ilyas, M. U., & Radha, H. (2012). A dynamic programming approach to maximizing a statistical measure of the lifetime of sensor networks. ACM Transactions on Sensor Networks, 8(2), 18.

    Article  Google Scholar 

  23. Vinh, T.-Q., Huu, P. N., & Miyoshi, T. (2011). A transmission range optimization algorithm to avoid energy holes in wireless sensor networks. IEICE Transactions on Communications E, 94B(11), 3026–3036.

    Google Scholar 

  24. Azad, A. K. M., & Kamruzzaman, J. (2011). Energy-balanced transmission policies for wireless sensor networks. IEEE Transactions on Mobile Computing, 10(7), 927–940.

    Article  Google Scholar 

  25. CC1000 Single Chip very low power RF transceiver. http://www.ti.com. Accessed September 17, 2012.

  26. CC2420 2.4 GHz IEEE 802.15.4/ZigBee-ready RF Transceiver. http://www.ti.com. Accessed September 17, 2012.

  27. Heinzelman, W. B. (2000). Application-specific protocol architectures for wireless networks. Ph.D. thesis. Massachusetts Institute of Technology.

  28. Sun, H., Wang, Y., & Chai, S. (2005). A universal approach for continuous or discrete nonlinear programmings with multiple variables and constraints. Applied Mathematics and Mechanics, 26(10), 1284–1292.

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgments

This work was supported in part by National Nature Science Foundation under Grant 61073164, China Postdoctoral Science Foundation under Grant 2011M500614, and the Fund of Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education under Grant 93K172012K05. The authors express sincere appreciation to the editors and the anonymous reviewers for their helpful comments.

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Correspondence to Bin Li.

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Zhang, J., Liu, Y., Sun, D. et al. Prolonging the lifetime of wireless sensor networks by utilizing feedback control. Wireless Netw 20, 2095–2107 (2014). https://doi.org/10.1007/s11276-014-0726-x

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