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Energy Balance Based Uneven Cluster Routing Protocol Using Ant Colony Taboo for Wireless Sensor Networks

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Abstract

To overcome the drawbacks of the short lifetime in wireless sensor networks (WSNs) caused by the imbalanced energy consumption, this paper proposes an efficient ant colony taboo based energy balance routing protocol using uneven cluster (ACTEBUC) for WSNs. The mechanism of temporary cluster head election is improved, the generation of random numbers is optimized, and the energy, distance and density factors are deduced into the threshold value. The real cluster heads are selected based on the node’s competition radius and communication cost that are used for the uneven clustering. Once finishing the cluster, ACTEBUC optimizes ant colony, and improves the probability of selecting next hop node, the pheromone update and the inspiring factor. The pheromone updating is added to the tasks of the forward ant to speed up the convergence rate. The path length is considered when pheromone updating is executed by the backward ant, the ants release more pheromones on the node which is closer to the destination node, which makes the destination node is more likely to be found and speeds up the convergence rate of the algorithm. Meanwhile, a route optimizing algorithm is proposed to increase network lifetime by adjusting the transmission route, and it finds the optimal path to minimize the communication energy consumption. The performance of the proposed algorithm is simulated using MATLAB. Comparing with the results of other algorithms, the simulation results show that the proposed algorithm can efficiently balance the energy consumption, and demonstrate the good performance of the proposed algorithms to increase network lifetime. Also ACTEBUC has the ability to enhance the data transmission reliability.

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References

  1. Fan, X. L., & Du, F. F. (2015). An efficient bypassing void routing algorithm for wireless sensor network. Journal of Sensors. doi:10.1155/2015/686809.

    Google Scholar 

  2. Yan, L. S., Pan, W., Luo, B., et al. (2009). Communication protocol based on optical low energy adaptive clustering hierarchy for hybrid optical wireless sensor networks. In Conference: Communications and Photonics Conference and Exhibition, 2009, SPIE OSA IEEE (Vol. 7633, pp. 763311-1–763311-6).

  3. Mohammad, M. H., & Jason, P. J. (2011). Survivable self- organization for prolonged lifetime in wireless sensor networks. International Journal of Distributed Sensor Networks, 2011(1), 1–11.

    Google Scholar 

  4. Hu, S. Z., Bao, D. W., Wang, B., et al. (2014). Clustering data gathering algorithm based on multiple cluster heads for wireless sensor networks. Journal of Electronics & Information Technology, 36(2), 403–408.

    Google Scholar 

  5. Fei, X., & Magill, E. H. (2008). Rule execution and event distribution middleware for PROSEN-WSN. In The second international conference on sensor technologies and applications (pp. 580–585).

  6. Hu, X. H., Luo, J., Xia, Z., et al. (2011). Adaptive algorithm of cluster head in wireless sensor network based on LEACH. In International conference on communication software and networks (pp. 14–18).

  7. Soro, S., & Heinzelman, W. B. (2005). Prolonging the lifetime of wireless sensor networks via unequal clustering. In Proceedings of the 19th international parallel and distributed processing symposium (pp. 8–17).

  8. Tang, J. S., & Wang, Y. (2013). Improved EEUC routing protocol for wireless sensor networks. Journal of Chongqing University of Posts and Telecommunications, 25(2), 172–177.

    Google Scholar 

  9. Chen, C. Q., Gu, X., Yu, J. G., et al. (2014). IDUC: An improved distributed unequal clustering protocol for wireless sensor networks. Wireless Algorithms, Systems, and Applications, 8491, 682–693.

    Google Scholar 

  10. Guo, S. C., Lu, Y., & Xu, D. G. (2010). Research on a routing algorithm for clustered wireless sensor networks. Journal on Communications, 31(8A), 63–69.

    Google Scholar 

  11. Heewook, S., Sangman, M., Ilyong, C., et al. (2015). Equal-size clustering for irregularly deployed wireless sensor networks. Wireless Personal Communications, 82(2), 995–1012.

    Article  Google Scholar 

  12. Pratyay, K., & Prasanta, J. (2014). Energy efficient clustering and routing algorithms for wireless sensor networks: Particle swarm optimization approach. Engineering Applications of Artificial Intelligence, 33, 127–140.

    Article  Google Scholar 

  13. Barceló, M., Correa, A., Vicario, J. L., et al. (2015). Joint routing, channel allocation and power control for real-life wireless sensor networks. Transactions on Emerging Telecommunications Technologies, 26, 945–956.

    Article  Google Scholar 

  14. Gupta, H. P., Rao, S. V., & Yadav, A. K. (2015). Geographic routing in clustered wireless sensor networks among obstacles. IEEE Sensors Journal, 15(5), 2984–2992.

    Article  Google Scholar 

  15. Habibi, J., Aghdam, A. G., & Ghrayeb, A. (2015). A framework for evaluating the best achievable performance by distributed lifetime-efficient routing schemes in wireless sensor networks. IEEE Transactions on Wireless Communications, 14(6), 3231–3245.

    Article  Google Scholar 

  16. Sharma, S., & Jena, S. K. (2015). Cluster based multipath routing protocol for wireless sensor networks. ACM SIGCOMM Computer Communication Review, 45(2), 15–20.

    Article  Google Scholar 

  17. Amiri, E., Keshavarz, H., Alizadeh, M., et al. (2014). Energy efficient routing in wireless sensor networks based on fuzzy ant colony optimization. International Journal of Distributed Sensor Networks. doi:10.1155/2014/768936.

    Google Scholar 

  18. Amgoth, T., & Jana, P. K. (2015). Energy and coverage-aware routing algorithm for wireless sensor networks. Wireless Personal Communications, 81, 531–545.

    Article  Google Scholar 

  19. Pan, M. S., & Liu, P. L. (2014). Low latency scheduling for converge cast in ZigBee tree-based wireless sensor networks. Journal of Network and Computer Applications, 46, 252–263.

    Article  Google Scholar 

  20. AlSkaif, T., Zapata, M. G., & Bellalta, B. (2015). Game theory for energy efficiency in wireless sensor networks: Latest trends. Journal of Network and Computer Applications, 54, 33–61.

    Article  Google Scholar 

  21. Malathi, L., Gnanamurthy, R., & Chandrasekaran, K. (2015). Energy efficient data collection through hybrid unequal clustering for wireless sensor networks. Computers & Electrical Engineering, 48, 358–370.

    Article  Google Scholar 

  22. Velmani, R., & Kaarthick, B. (2015). An efficient cluster-tree based data collection scheme for large mobile wireless sensor networks. IEEE Sensors Journal, 15(4), 2377–2390.

    Article  Google Scholar 

  23. Sung, T.-W., & Yang, C.-S. (2014). Voronoi-based coverage improvement approach for wireless directional sensor networks. Journal of Network and Computer Applications, 39, 202–213.

    Article  Google Scholar 

  24. Ye, W., Heidemann, I., & Estrin, D. (2008). An energy-efficient MAC protocol for wireless sensor networks. In Global telecom conference, 2005. GLOBECOM’05 (Vol. 3, pp. 1567–1576).

  25. Sung, T. W., Lu, Y. T., Lin, F. T., et al. (2015). Direction control using delaunay triangulation for coverage improvement in directional sensor network. In Third international conference on robot, vision and signal processing (pp. 290–293).

  26. Huang, H. Q., Shen, J., Yao, D. Y., et al. (2009). An energy driven adaptive cluster head rotation algorithm for wireless sensor networks. Journal of Electronics & Information Technology, 31(5), 1040–1044.

    Google Scholar 

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Acknowledgements

This work was supported by Natural Science Foundation of China (61503300 and 61502387), Natural Science Basic Research Plan in Shaanxi Province (2014KW03-02), China Postdoctoral Science Foundation (2014M560801).

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Correspondence to Lin Wang.

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Fan, X., Jia, H., Wang, L. et al. Energy Balance Based Uneven Cluster Routing Protocol Using Ant Colony Taboo for Wireless Sensor Networks. Wireless Pers Commun 97, 1305–1321 (2017). https://doi.org/10.1007/s11277-017-4567-7

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