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A Low Energy Multi-hop Routing Protocol Based on Programming Tree for Large-Scale WSN

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10736))

Abstract

In large-scale conditions, due to the number of nodes and the spread of space range are larger, the energy consumption of sensor nodes in the network is more serious, which proposes the higher energy requirements on WSN routing protocols. In this paper, the energy saving scheme of WSN routing protocols is analyzed and classified, and we find that the traditional routing protocols have a lot of room for improvement. In these protocols, cluster head selection usually adopts a random selection method by considering the cluster head rotation, but the cluster head can’t keep a reasonable distribution. At the same time, the lack of reasonable planning of the communication path between cluster heads causes a large communication overhead. For this, we put forward a low energy adaptive clustering multi-hop routing protocol based on programming tree (LEACH-PT). The routing protocol takes consideration in the structure within the cluster, the remaining energy of nodes and so on. Based on these factors, the protocol makes the selection of cluster head optimal. Through the method of programming tree, the protocol builds the routing path of the cluster head. Analysis and simulation results show that our protocol provides better balance in energy consumption among nodes and can prolong network lifetime significantly.

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Acknowledgments

This work is supported by the China Aviation Science Foundation (NO. 20101952021), the Fundamental Research Funds for the Central Universities (NO. NZ2013306) and the Key Project supported by Medical Science and technology development foundation, Nanjing Department of Health (NO. YKK15170).

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Correspondence to Feng Xu .

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Xu, F., Hou, Y., Qian, G., Yao, Y. (2018). A Low Energy Multi-hop Routing Protocol Based on Programming Tree for Large-Scale WSN. In: Zeng, B., Huang, Q., El Saddik, A., Li, H., Jiang, S., Fan, X. (eds) Advances in Multimedia Information Processing – PCM 2017. PCM 2017. Lecture Notes in Computer Science(), vol 10736. Springer, Cham. https://doi.org/10.1007/978-3-319-77383-4_93

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  • DOI: https://doi.org/10.1007/978-3-319-77383-4_93

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-77382-7

  • Online ISBN: 978-3-319-77383-4

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