A novel deep neural networks based path prediction (original) (raw)

References

  1. Zou, Y., Quan, L.: A new service-oriented grid-based method for aiot application and implementation. Mod. Phys. Lett. B 31(19–21), 1740064 (2017)
    Article Google Scholar
  2. Wang, Y., Huang, S., Ji, Z.: Operation management of daily economic dispatch using novel hybrid particle swarm optimization and gravitational search algorithm with hybrid mutation strategy. Mod. Phys. Lett. B 31(19–21), 1740099 (2017)
    Article MathSciNet Google Scholar
  3. Xu, B., Wang, Y., Ji, Z.: Knowledge network model of the energy consumption in discrete manufacturing system. Mod. Phys. Lett. B 31(19–21), 1740100 (2017)
    Article Google Scholar
  4. Zhang, M., Ji, Z., Wang, Y.: Artificial bee colony algorithm with dynamic multi-population. Mod. Phys. Lett. B 31(19–21), 1740087 (2017)
    Article Google Scholar
  5. Leu, J., Chiang, T., Yu, M., Su, K.: Energy efficient clustering scheme for prolonging the lifetime of wireless sensor network with isolated nodes. IEEE Commun. Lett. 19, 259–262 (2015)
    Article Google Scholar
  6. Pal, V., Singh, G., Yadav, R.P.: Balanced cluster size solution to extend lifetime of wireless sensor networks. IEEE Internet Things J. 2, 399–401 (2015)
    Article Google Scholar
  7. Chidean, M.I., Morgado, E., Sanroman-Junquera, M., Ramiro-Bargueno, J., Ramos, J., Caamano, A.J.: Energy efficiency and quality of data reconstruction through data-coupled clustering for self-organized large-scale wsns. IEEE Sens. J. 16, 5010–5020 (2016)
    Article Google Scholar
  8. Lee, J., Kao, T.: An improved three-layer low-energy adaptive clustering hierarchy for wireless sensor networks. IEEE Internet Things J. 3, 951–958 (2016)
    Article Google Scholar
  9. El Alami, H., Najid, A.: Ech: an enhanced clustering hierarchy approach to maximize lifetime of wireless sensor networks. IEEE Access 7, 107142–107153 (2019)
    Article Google Scholar
  10. Gharaei, N., Al-Otaibi, Y.D., Butt, S.A., Sahar, G., Rahim, S.: Energy-efficient and coverage-guaranteed unequal-sized clustering for wireless sensor networks. IEEE Access 7, 157883–157891 (2019)
    Article Google Scholar
  11. Lin, H., Wang, L., Kong, R.: Energy efficient clustering protocol for large-scale sensor networks. IEEE Sens. J. 15, 7150–7160 (2015)
    Article Google Scholar
  12. Chamam, A., Pierre, S.: On the planning of wireless sensor networks: energy-efficient clustering under the joint routing and coverage constraint. IEEE Trans. Mob. Comput. 8, 1077–1086 (2009)
    Article Google Scholar
  13. Pachlor, R., Shrimankar, D.: Lar-ch: a cluster-head rotation approach for sensor networks. IEEE Sens. J. 18, 9821–9828 (2018)
    Article Google Scholar
  14. Hong, Z., Wang, R., Li, X.: A clustering-tree topology control based on the energy forecast for heterogeneous wireless sensor networks. IEEE/CAA J. Autom. Sin. 3, 68–77 (2016)
    Article MathSciNet Google Scholar
  15. Tarhani, M., Kavian, Y.S., Siavoshi, S.: Seech: scalable energy efficient clustering hierarchy protocol in wireless sensor networks. IEEE Sens. J. 14, 3944–3954 (2014)
    Article Google Scholar
  16. Lee, W., Nguyen, M.V., Verma, A., Lee, H.S.: Schedule unifying algorithm extending network lifetime in s-mac-based wireless sensor networks. IEEE Trans. Wirel. Commun. 8, 4375–4379 (2009)
    Article Google Scholar
  17. Lin, Chia-Hung, Tsai, Ming-Jer: A comment on “heed: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Trans. Mob. Comput. 5, 1471–1472 (2006)
    Article Google Scholar
  18. Wang, T., Zhang, G., Yang, X., Vajdi, A.: Genetic algorithm for energy-efficient clustering and routing in wireless sensor networks. J. Syst. Softw. 146, 196–214 (2018)
    Article Google Scholar
  19. Ahmed, G., Zou, J., Fareed, M.M.S., Zeeshan, M.: Sleep-awake energy efficient distributed clustering algorithm for wireless sensor networks. Comput. Electr. Eng. 56, 385–398 (2016)
    Article Google Scholar
  20. Shankar, T., Shanmugavel, S., Rajesh, A.: Hybrid hsa and pso algorithm for energy efficient cluster head selection in wireless sensor networks. Swarm Evol. Comput. 30, 1–10 (2016)
    Article Google Scholar
  21. Goswami, P., Yan, Z., Mukherjee, A., Yang, L., Routray, S., Palai, G.: An energy efficient clustering using firefly and hml for optical wireless sensor network. Optik 182, 181–185 (2019)
    Article Google Scholar
  22. Wang, Q., Xu, K., Takahara, G., Hassanein, H.: On lifetime-oriented device provisioning in heterogeneous wireless sensor networks: approaches and challenges. IEEE Netw. 20, 26–33 (2006)
    Article Google Scholar
  23. Ding, X.-X., Ling, M., Wang, Z.-J., Song, F.-L.: Dk-leach: an optimized cluster structure routing method based on leach in wireless sensor networks. Wirel. Pers. Commun. 96(4), 6369–6379 (2017)
    Article Google Scholar
  24. Han, R., Yang, W., Wang, Y., You, K.: Dce: a distributed energy-efficient clustering protocol for wireless sensor network based on double-phase cluster-head election. Sensors 17(5), 998 (2017)
    Article Google Scholar
  25. Mann, P.S., Singh, S.: Energy efficient clustering protocol based on improved metaheuristic in wireless sensor networks. J. Netw. Comput. Appl. 83, 40–52 (2017)
    Article Google Scholar
  26. Ha, I., Djuraev, M., Ahn, B.: An optimal data gathering method for mobile sinks in wsns. Wireless Pers. Commun. 97(1), 1401–1417 (2017)
    Article Google Scholar
  27. You, X., Li, X., Xu, Y., Feng, H., Zhao, J.: Toward packet routing with fully-distributed multi-agent deep reinforcement learning. arXiv arXiv:1905.03494 (2019) (preprint)

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