Energy Efficient Clustering Routing Algorithm Based on Improved FCM

SUN Qian; MENG Xiang-yue; GAO Zhuo-qi

doi:10.12263/newIT.2024.05.002

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Energy Efficient Clustering Routing Algorithm Based on Improved FCM

RESEARCH PAPER | 更新时间：2025-05-23

- Energy Efficient Clustering Routing Algorithm Based on Improved FCM
- New Generation of Information Technology Vol. 7, Issue 5, Pages: 6-11(2024)
- 作者机构：
  
  北京工商大学计算机与人工智能学院，北京 100048
- 作者简介：
- 基金信息：
- DOI：10.12263/newIT.2024.05.002
  CLC： TP393
- Published：15 May 2024
- 稿件说明：
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孙茜, 孟祥越, 高卓琪. 基于改进FCM的节能分簇路由算法[J]. 新一代信息技术, 2024, 7(5): 06-11

SUN Qian, MENG Xiang-yue, GAO Zhuo-qi. Energy Efficient Clustering Routing Algorithm Based on Improved FCM[J]. New Generation of Information Technology, 2024, 7(5): 06-11
孙茜, 孟祥越, 高卓琪. 基于改进FCM的节能分簇路由算法[J]. 新一代信息技术, 2024, 7(5): 06-11 DOI： 10.12263/newIT.2024.05.002.

SUN Qian, MENG Xiang-yue, GAO Zhuo-qi. Energy Efficient Clustering Routing Algorithm Based on Improved FCM[J]. New Generation of Information Technology, 2024, 7(5): 06-11 DOI： 10.12263/newIT.2024.05.002.

摘要

无线传感器网络是物联网的重要组成部分，其能效和网络寿命问题是当前的研究热点。分簇路由算法可有效解决能效问题，高效的簇头选取和传输策略可降低网络能耗并提高网络的稳定性和可持续性。本文提出了一种基于模糊聚类的分簇数量和簇头选取方法。针对模糊C均值聚类算法需预设聚类数量且聚类算法运行完成后输出信息中不包含簇头信息的问题进行了改进，并对不同监测区域面积下的网络性能进行了仿真分析。仿真结果表明，本文所提算法在网络能耗和网络寿命方面都有较优的表现。

Abstract

The wireless sensor network is a crucial component of the Internet of Things

and issues related to energy efficiency and network longevity are currently focal points of research. Cluster routing algorithms can effectively address energy efficiency challenges

while efficient cluster head selection and transmission strategies can reduce network energy consumption and enhance both stability and sustainability. This paper proposes a method for determining the number of clusters and selecting cluster heads based on fuzzy clustering. It improves upon the fuzzy C-means clustering algorithm

which requires pre-setting the number of clusters and does not provide cluster head information in its output after execution. Additionally

simulations are conducted to analyze network performance under varying monitoring area sizes. Simulation results indicate that the proposed algorithm demonstrates superior performance in terms of both network energy consumption and lifespan.

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references

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