利用带宽有效聚类的WSN数据聚合优化算法

发布时间：2018-03-31 03:11

本文选题：带宽有效聚类　切入点：数据聚合　出处：《控制工程》2017年01期

【摘要】：针对无线传感器网络(wireless sensor network,WSN)中带宽资源有限而节点收集数据量大的问题,为了提高带宽利用率,提出了基于带宽有效聚类的数据聚合(bandwidth efficient clustering based data aggregation BECDA)算法。首先,将随机分布的异构节点编进簇类的编号中;然后,利用簇头对可变簇类成员生成的数据包进行聚合;最后,对随机分布的拥有可变数据生成率的节点进行类内和类间聚合以获取最优方案。利用包中的相关数据对建立在节点数据上的聚合函数进行测试,仿真结果表明,相比基于双重聚类的数据聚合(two tier cluster based data aggregation,TTCDA)、高能效聚类的数据聚合(energy efficient clustering and data aggregation,EECDA)算法,提出的BECDA算法的数据包聚合性能在吞吐量、平均能耗、包投递率方面均有显著提升。
[Abstract]:Aiming at the problem of limited bandwidth resource and large amount of data collected by nodes in wireless sensor network (WSNs), in order to improve bandwidth utilization, an algorithm of data aggregation bandwidth efficient clustering based data aggregation BECDA based on bandwidth efficient clustering is proposed.First, the randomly distributed heterogeneous nodes are compiled into the number of the cluster class; then, the cluster head is used to aggregate the data packets generated by the members of the variable cluster class.Intra-class and inter-class aggregation of randomly distributed nodes with variable data generation rate is performed to obtain the optimal scheme.The aggregation function based on node data is tested by using the relevant data in the package. The simulation results show that compared with the data aggregation based on double clustering, two tier cluster based data aggregation based on high energy efficiency clustering can aggregate energy, efficient clustering and data aggregation.The packet aggregation of the proposed BECDA algorithm can significantly improve the throughput, average energy consumption and packet delivery rate.
【作者单位】：周口师范学院计算机科学与技术学院;周口师范学院数学与统计学院;
【基金】：河南省软科学研究计划项目(132400410934)
【分类号】：TP212.9;TN929.5

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