| 基于节点分布均匀度模型的加权能量检测GAF算法 |
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| 引用本文： | 马学森,刘会平,韩江洪,魏振春. 基于节点分布均匀度模型的加权能量检测GAF算法[J]. 电子测量与仪器学报, 2013, 0(12): 1120-1126 |
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| 作者姓名： | 马学森 刘会平 韩江洪 魏振春 |
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| 作者单位： | [1]合肥工业大学计算机与信息学院,合肥230009 [2]中国科学院上海微系统与信息技术研究所无线传感网与通信重点实验室,上海200050 |
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| 基金项目： | 广东省教育部产学研结合（20118090400524）、安徽省高校省级自然科学研究重点（KJ2012A233）、中国科学院上海微系统与信息技术研究所无线传感网与通信重点实验室开放课题（2013003）、合肥工业大学国家级大学生创新基金（201210359018）资助项目 |
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| 摘 要： | 存分析了传统GAF算法在选举簇头和虚拟单元格方格划分不足的基础上，提出了一种节点分布均匀度模型的加权能量检测GAF算法，在对虚拟单元格形状改进的基础上，建直节点分布均匀度模型，进一步对虚拟单元格的划分提供参考，同时对算法中簇头选举综合考虑节点剩余能量及其与虚拟单元格内物理节点的质心间距，能有效解决节点能量消耗不均衡问题。最后以GPSR作为GAF算法的底层通信协议进行仿真，结果表明该算法有效地节省了节点的能量，延长了网络的牛存周期。
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| 关 键 词： | 分簇算法 分布均匀度 GAF算法 能量检测 |
GAF algorithm based on node uniformity model and weighted energy detection |
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| Ma Xuesen,Liu Huiping,Han Jianghong,Wei Zhenchun. GAF algorithm based on node uniformity model and weighted energy detection[J]. Journal of Electronic Measurement and Instrument, 2013, 0(12): 1120-1126 |
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| Authors: | Ma Xuesen Liu Huiping Han Jianghong Wei Zhenchun |
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| Affiliation: | 1. School of Computer ＆ Information, Hefei University of Technology, Hefei 230009, China;2. Key Laboratory of Wireless Sensor Network ＆ Communication,Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China) |
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| Abstract: | On the basis of analyzing shortcomings of the cluster head election and virtual cell division of traditional GAF algorithm, a GAF algorithm based on node uniformity model and weighted energy detection is proposed. On the basis of improving the shape of virtual cell, we build the node uniformity model and further provide the reference for virtual cell division. And we also consider the residual energy of the nodes and the distance between the cluster and the center of mass of nodes in virtual cell. It can solve the unbalanced energy consumption of nodes effectively. We use GPSR as the lower layer communication protocols of GAF algorithm, and the simulation results show that the improved algorithm can save the energy of the nodes effectively and prolong the network lifetime. |
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| Keywords: | clustering algorithm node uniformity GAF algorithm energy detection |
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