Abstract
Energy consumption has been an important content of wireless sensor network research in recent years, and node energy consumption can be effectively reduced by optimizing routing algorithms. Aiming at the problem of random clustering and uneven clustering in the LEACH algorithm, which leads to unbalanced energy, a routing algorithm for uniform clustering is proposed. The network is evenly clustered, and reasonable cluster heads are selected by competition in the clustering stage of the network. The data transmission path is optimized. The polling control mechanism is introduced into the intra-cluster communication during the data communication stage, which is carried out by combining single-hop and multi-hop. The simulation results show that the algorithm can effectively reduce network energy consumption, extend network lifetime, and improve throughput.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Wang, T.S., et al.: Genetic algorithm for energy-efficient clustering and routing in wireless sensor networks. Syst. Softw. 146, 196–214 (2018)
Pan, J.Q., Feng, Y.Z.: Improved LEACH sensor network cluster routing algorithm. J. Jilin Univ. (Sci. Edition) 56(6), 1476–1482 (2018)
Heinzelman, W.R., Chandrakasan, A., Balakrishnan, H.: Energy-efficient communication protocol for wireless microsensor networks. In: Proceedings of the 33rd Annual Hawaii International Conference on System Sciences, Hawaii, pp. 3005–3014. IEEE (2000)
Huang, L.X., et al.: Improved LEACH protocol algorithm based on energy balanced and efficient WSN. J. Commun. 38(S2), 164–169 (2017)
Zhu, S.X., Ma, H.F., Sun, G.L.: An energy-efficient wireless sensor network improved LEACH protocol. J. Harbin Univ. Sci. Technol. 26(3), 91–98 (2021)
Singh, S.P., Sharma, S.C.: An improved cluster-based routing algorithm for energy optimisation in wireless sensor networks. Int. J. Wireless Mobile Comput. 14(1), 82–89 (2018)
Zhang, Y.Q.: Research on uniform clustering routing algorithm for wireless sensor networks based on K-means. Control Eng. 22(6), 1181–1185 (2015)
Senthilkumar, C., Manickam, J.P.: A path-aware clustering mechanism for energy-efficient routing protocol in wireless sensor networks. J. Comput. Theor. Nanosci. 14(11), 5478–5483 (2017)
Li, Y.N., Xu, F.T., Chen, J.X.: Clustering optimization strategy for WSNs Based on LEACH. Chinese J. Sens. Actuators 27(5), 670–674 (2014)
Wu, X.N., et al.: Clustering Routing protocol based on improved particle swarm optimization algorithm in WSN. J. Commun. 40(12), 114–123 (2019)
Huang, W., Ling, Y., Zhou, W.: An improved LEACH routing algorithm for wireless sensor network. Int. J. Wireless Inf. Netw. 25(3), 323–331 (2018). https://doi.org/10.1007/s10776-018-0405-4
Bano, S., Khan, M.: A survey of data clustering methods. Int. J. Adv. Sci. Technol. 113, 133–142 (2018)
Zhang, X.L.: Improved IoT Energy Consumption Balance Routing Algorithm Based on LEACH Protocol. Jilin University, Jilin (2016)
Al-Baz, A., El-Sayed, A.: A new algorithm for cluster head selection in LEACH protocol for wireless sensor networks. Int. J. Commun. Syst. 31(1), 1–13 (2018)
Liu, L.J., et al.: Research on FPGA WSN polling access control protocol. J. Commun. 37(10), 181–187 (2016)
Sony, C.T., Sangeetha, C.P., Suriyake, C.D.: Multi-hop LEACH protocol with modified cluster head selection and TDMA schedule for wireless sensor networks. In: Communication Technologies (GCCT), pp. 539–543. IEEE (2015)
Wang, B., Fu, D.S.: Improvement of LEACH routing protocol for wireless sensor networks. Instrum. Technique Sens. 8, 71–74 (2016)
Acknowledgment
This work was supported by the Plateau Discipline Innovation Team Project of the Harbin University of Commerce.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Yu, J., Bai, Y. (2022). An Improved Clustering Routing Algorithm Based on Leach. In: Hassanien, A.E., Xu, Y., Zhao, Z., Mohammed, S., Fan, Z. (eds) Business Intelligence and Information Technology. BIIT 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 107. Springer, Cham. https://doi.org/10.1007/978-3-030-92632-8_17
Download citation
DOI: https://doi.org/10.1007/978-3-030-92632-8_17
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-92631-1
Online ISBN: 978-3-030-92632-8
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)