Clustering method of chaotic particle swarm optimization sensor networks based on multi-factor conflict
In order to solve the multi-factor conflict problem in cluster head election process, and to ensure the optimization of cluster head election and prolong the network life cycle, a chaotic particle swarm optimization method based on multi-factor conflict is proposed to cluster sensor networks. The object of study is a sensor network with hierarchical clustering network topology, which includes cluster member nodes, cluster head nodes and sink nodes. The energy consumption model of data receiving and processing in network nodes is constructed. Four kinds of multi-factor collision problems of node residual energy, energy balance between nodes and distance between base stations, and probability of the node acting as cluster head are discussed. An energy balance index based on standard deviation of node residual energy is introduced to construct an adaptive degree function to obtain the relationship between the current adaptive degree of particles and the previous adaptive degree of particles. Then, the inertia weight is determined. The chaotic particle swarm optimization algorithm based on adaptive inertia weight is used to optimize the cluster head election. The nodes in the communication area are regarded as the cluster members. The number of cluster heads can meet the optimal number of cluster heads, which further improves the energy efficiency of the network. The simulation results show that the death time of the first node, half node and the last node of the sensor network clustered by this method is 83.33%, 34.14% and 43.14% longer than that of LEACH method, respectively. The energy consumption of the sensor network clustering is low, the network life cycle is long and the clustering effect is good.
Keywords
multi-factor conflict,
chaotic particle swarm optimization,
sensor network,
clustering method,
energy balanceAuthors
| Lijun Liu | College of Computer Science & Technology, Taizhou University | tsjncs@sohu.com |
| Jin Qian | College of Computer Science & Technology, Taizhou University | qianjin@tzu.edu.cn |
| Aiping Zhou | College of Computer Science & Technology, Taizhou University | apzhou163@163.com |
| Ye Zhu | College of Computer Science & Technology, Taizhou University | zhu99ye5289@163.com |
Всего: 4
References
Rao P.C.S., Jana P.K., and Banka H.A. // Wirel. Netw. - 2017. - V. 23. - No. 7. - P. 2005-2020.
Kang T. and Wei S.F. // Int. Tech. Sens. - 2019. - No. 1. - P. 122-125.
Zhong D.F., Xue J.J., He F., et al. // Chin. High Technol. Lett. - 2017. - V. 27. - No. 6. - P. 530-536.
Du Y.W., Feng K., and Lian Y.X. // J. Chin. Comput. Syst. - 2017. - V. 38. - No. 10. - P. 2221-2225.
He W., Ling H., Zhang Z., et al. // Int. J. Geogr. Inform. Sci. - 2018. - V. 32. - No. 4. - P. 827-846.
Li G. and Wang W. // Control Eng. Chin. - 2017. - V. 24. - No. 7. - P. 1359-1365.
Tian S.Q., Lang B.H. and Han T.L. // J. Jilin Univ. (Inf. Sci. Ed.). - 2018. - V. 36. - No. 1. - P. 19-21.
Dong D.D., Liu B.F., Dong X., et al. // Chin. J. Sens. Actuator. - 2017. - V. 30. - No. 12. - P. 1918- 1924.
Li X.W. // Comput. Simulation. - 2018. - V. 35. - No. 3. - P. 205-209.
Liu Z.Z. and Liu Y. // J. Chin. Comput. Syst. - 2017. - V. 38. - No. 10. - P. 2207-2210.
Sun Y.J. // Wool Text. J. - 2017. - V. 45. - No. 9. - P. 80-85.
Yu Q., Li J.H., Zhao Q.F., et al. // Elect. Meas. Instrum. - 2017. - V. 54. - No. 13. - P. 110-114.
Wu B., Cui C., Yu J., et al. // Comput. Sci. - 2017. - No. 2. - P. 157-162.
Li L.S. and Zhang X.J. // Comput. Eng. Appl. - 2018. - V. 54. - No. 9. - P. 139-144.
Zhao J., Yu Z.G., Feng X., et al. // J. Chin. Acad. Electron. Inf. Technol. - 2018. - V. 13. - No. 03. - P. 38-45.
Li Z., Chen Y.F., Zhang B., et al. // J. Pow. Supply. -2017. - V. 15. - No. 3. - P. 148-155.
Peng P., Cheng H.X., Chen X.C., et al. // Chin. J. Pow. Source. - 2017. - V. 41. - No. 11. - P. 1541- 1544.
Hu Y.G., Meng X.L., Zhao C., et al. // Automation Instrum. - 2015. - No. 6. - P. 14-15.
Wang C.H., Shen W.N., and Hu H.S. // J. Jilin Univ. (Sci. Ed.). - 2018. - V. 56. - No. 3. - P. 169-176.
Dong H.J., Wei S.Y., Liu X.C., et al. // Comput. Sci. - 2018. - V. 45. - No. 1. - P. 14-23.
Chen J. // Comput. Simulat. - 2017. - V. 34. - No. 10. - P. 277-280.
Atangana A. and Alqahtani R.T. // Math. Modell. Nat. Ph. - 2019. - V. 14. - No. 3. - P. 313.
Saad K.M., Baleanu D., and Atangana A. // Comput. Appl. Math. - 2018. - V. 37. - No. 4. - P. 5203-5216.
Xiong Z. et al. // Multimedia Tools Appl. - 2019. - V. 78. - No. 22. - P. 31035-31055.
Citil H.G. // Appl. Math. Nonlinear Sci. - 2019. - V. 4. - No. 2. - P. 407-416.
Mundewadi R.A. and Kumbinarasaiah S. // Appl. Math. Nonlinear Sci. - 2019. - V. 4. - No. 2. - P. 395-406.
Naeem M., Siddiqui M.K., Guirao J.L.G., et al. // Appl. Math. Nonlinear Sci. - 2020. - V. 3. - No. 1. - P. 209-228.
Venkatesha S.B. // Appl. Math. Nonlinear Sci. - 2020. - V. 5. - No. 1. - P. 85-92.
