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Journal of Robotics
Volume 2018, Article ID 1487908, 8 pages
https://doi.org/10.1155/2018/1487908
Research Article

Method for Effectively Utilizing Node Energy of WSN for Coal Mine Robot

1Xuzhou Institute of Technology, Xuzhou, Jiangsu 221111, China
2School of Mechanical and Electrical Engineering, China University of Mining and Technology, Xuzhou, Jiangsu 221116, China

Correspondence should be addressed to Xiliang Ma; moc.anis@818amlx

Received 3 October 2017; Accepted 13 December 2017; Published 11 January 2018

Academic Editor: L. Fortuna

Copyright © 2018 Xiliang Ma and Ruiqing Mao. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. X. Ma and H. Zhu, “Gas concentration prediction based on the measured data of a coal mine rescue robot,” Journal of Robotics, vol. 2016, pp. 1–10, 2016. View at Publisher · View at Google Scholar
  2. A. E. Forster and A. L. Murphy, “Exploiting reinforcement learning for multiple sink routing in WSN,” in Proceedings of the IEEE Internatonal Conference on Mobile Adhoc and Sensor Systems, MASS, Italy, October 2007. View at Publisher · View at Google Scholar · View at Scopus
  3. P. Ciciriello, L. Mottola, and G. P. Picco, “Efficient routing from multiple sources to multiple sinks in wireless sensor networks,” Wireless Sensor Networks, vol. 4373, pp. 34–50, 2007. View at Google Scholar · View at Scopus
  4. M. Meng, X. Wu, B.-S. Jeong, S. Lee, and Y.-K. Lee, “Energy efficient routing in multiple sink sensor networks,” in Proceedings of the 5th International Conference on Computational Science and Its Applications (ICCSA '07), pp. 561–566, IEEE, August 2007. View at Publisher · View at Google Scholar
  5. J.-M. Dricot, S. Van Roy, G. Ferrari, F. Horlin, and P. De Doncker, “Impact of the environment and the topology on the performance of hierarchical body area networks,” EURASIP Journal on Wireless Communications and Networking, vol. 2011, no. 1, pp. 1–17, 2011. View at Publisher · View at Google Scholar · View at Scopus
  6. X. Yan, Y. Zhang, H. Tang, and S. Li, “An ETBG optimization algorithm based on analytic hierarchy process in WSS,” in Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013), China, March 2013. View at Publisher · View at Google Scholar
  7. R. R. Yager, “Weighted maximum entropy OWA aggregation with applications to decision making under risk,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 39, no. 3, pp. 183–189, 2009. View at Publisher · View at Google Scholar · View at Scopus
  8. J. K. Goyal and K. S. Nagla, “A new approach of path planning for mobile robots,” in Proceedings of the 3rd International Conference on Advances in Computing, Communications and Informatics (ICACCI '14), pp. 863–867, IEEE, New Delhi, India, September 2014. View at Publisher · View at Google Scholar · View at Scopus
  9. X. Shi, Q. Ran, M. Fan, H. Yu, and L. Wang, “Dynamic weighted DV-Distance algorithm for wireless sensor networks,” Chinese Journal of Scientific Instrument, vol. 34, no. 9, pp. 1975–1981, 2013. View at Google Scholar
  10. S. L. Zheng, H. Che, Y. Q. Fan, D. Hu, and X. Xiao, “Agent-based mobile sink routing algorithm in wireless sensor networks,” Journal of Electronic Measurement and Instrument, vol. 27, no. 2, pp. 127–134, 2013. View at Publisher · View at Google Scholar
  11. H. Zhao, Z. H. Hu, and Y. Wwn, “ACS based differentiated service routing algorithm in wireless sensor network,” Journal on Communications, vol. 34, no. 10, pp. 106–115, 2013. View at Google Scholar
  12. J. Elias, “Optimal design of energy-efficient and cost-effective wireless body area networks,” Ad Hoc Networks, vol. 13, pp. 560–574, 2014. View at Publisher · View at Google Scholar · View at Scopus
  13. L. H. Yan and Y. Y. HE, “Robust approach foe holes recovery of wireless sensor networks,” Computer Science, vol. 44, no. 2, pp. 123–128, 2017. View at Google Scholar
  14. L. F. Liu, J. G. Wu, Z. Q. Zou, H. Chen, and L. Niu, “opology self-cure algorithm aiming at node failure problem in wireless sensor networks,” Journal of Southeast University, vol. 39, no. 4, pp. 695–699, 2009. View at Publisher · View at Google Scholar · View at Scopus
  15. A. Fortuna, L. Frasca, M. Iachello, M., and V. T. Pham, “Robustness to noise in synchronization of network motifs: Experimental results,” An Interdisciplinary Journal of Nonlinear Science, vol. 22, no. 4, Article ID 043106, 2012. View at Google Scholar