Abstract:

In order to better resist the rapid consumption of network energy and reduce the impact of unreliable links on the data collection of the Wireless Sensors Networks（WSNs） system to improve the accuracy of data reconstruction, this paper proposes a Multi-parameter Data Reconstruction Method based on Energy Efficient（MDR）. This method firstly uses mobile intelligent computing to give the multi-hop function relationship between sensor nodes to determine the proportional relationship between sensor nodes. Secondly, it designs a low-coherence observation matrix through a sparse matrix, suppresses the impact of data packet loss rate on the entire sensor networks system, and improves the accuracy of data reconstruction at the sink node. Again, the high reliability of data transmission between clusters is achieved through the confirmation mechanism based on the data forwarding strategy, and the reliable delivery of multipath routing data between nodes is completed. Simulation experiments show that when the data packet loss rate is 40%, the data reconstruction accuracy error of MDR is still less than 5%; when compared with other algorithms, the number of data forwarding is reduced by 10.36%, and the average network energy consumption is reduced by 13.29%, which verifies the effectiveness and materiality of the algorithm in this paper.

Key words: wireless sensor networks, data reconstruction, reconstruction error, packet loss rate, networks lifetime

摘要：

为了更好地抵制网络能量快速消耗和降低不可靠链路对无线传感器网络系统数据收集的影响以提高数据重构精度，提出了一种基于能量有效的多参数数据重构方法（Multi-parameter Data Reconstruction Method based on Energy Efficient，MDR）。利用移动智能计算给出传感器节点之间多跳函数关系以确定传感器节点之间比例关系；通过稀疏矩阵设计一种低相干性的观测矩阵，抑制数据丢包率对整个传感网系统的影响，提高汇聚节点数据重构精度；通过基于数据转发策略确认机制实现簇间数据传输的高可靠性，完成了节点间多路径路由数据的可靠交付。仿真实验表明，在数据丢包率为40%的情况下，MDR的数据重构精度误差仍小于5%；在与其他算法比对时，其数据转发次数降低了10.36%，平均网络能耗降低了13.29%，从而验证了该算法的有效性和实效性。

关键词: 无线传感器网络, 数据重构, 重构误差, 丢包率, 网络生存周期