基于聚类划分机制的无线传感网数据传输算法

发布时间：2018-05-27 17:07

  本文选题：无线传感网络 + 数据优化汇聚　； 参考：《计算机工程与设计》2017年05期

【摘要】：为解决当前无线传感网络数据传输算法的数据汇聚稳定性不高,且难以根据链路抖动实时调整传输链路的不足,提出基于聚类划分机制的无线传感网络数据传输算法。通过聚类划分机制,将网络中能量覆盖水平较强的节点进行最优聚合,实现最佳簇头节点对网络覆盖区域的划分,减轻分区内数据汇聚的压力;综合考虑节点数据汇聚过程中的能量及拓扑距离对数据汇聚的影响,获取节点传输过程中的距离-能量阈值,对路由进行优化筛选,实现数据汇聚链路的动态实时更新;通过链路优化筛选机制,对数据汇聚过程优化,降低汇聚过程中的链路抖动。仿真结果表明,与DAAS算法、DAAS_plus算法相比,所提算法能够降低数据链路的抖动,具备更高的网络稳定运行时间与更低的数据拥塞度。
[Abstract]:In order to solve the problem that the data convergence stability of the current wireless sensor network data transmission algorithm is not high, and it is difficult to adjust the transmission link according to the link jitter in real time, a data transmission algorithm based on clustering and partitioning mechanism is proposed. Through the clustering mechanism, the nodes with strong energy coverage in the network are optimally aggregated to realize the optimal cluster head node partition of the network coverage area, and to reduce the pressure of data convergence in the area. Considering the influence of energy and topological distance in the process of node data aggregation, the distance energy threshold in the process of node transmission is obtained, the route is optimized and filtered, and the dynamic real-time update of data convergence link is realized. Through the link optimization screening mechanism, the data aggregation process is optimized to reduce the link jitter in the convergence process. The simulation results show that compared with the DAAS algorithm, the proposed algorithm can reduce the jitter of the data link, and has higher stable running time and lower data congestion.
【作者单位】： 荆楚理工学院电子信息工程学院;
【分类号】：TN929.5;TP212.9
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本文编号：1943043