WS N中一种基于网络效益最大化的数据收集方案

摘要

Data gathering is one of hot research topics in wireless sensor networks.Aiming at the problems of too large energy consumption and low accuracy in data gathering the existing data gathering methods have,we propose a data gathering scheme which is based on network utilitymaximisation.First,the scheme collects the measurements of the perception data of each node based on compressive sampling,and then encodes the measurements with Gaussian random matrix at the locations the nodes are fused and followed by transmission,at last,it models the encoded measurement transmission problem as a network utility maximisation problem,and uses Lagrange multiplier method to obtainthe approximate optimal solution.Simulation experimental results show that the proposed method is effective and superior to the traditional methods in terms of the accuracy of data reconstruction and the lifecycle of network.%数据收集问题是无线传感网中的研究热点之一。针对现有的数据收集方法能耗过大以及数据收集精度低下的问题，提出一种基于网络效益最大化的数据收集方案。首先基于压缩采样得到各个节点感知数据的测量值，然后在融合节点处采用随机高斯矩阵对测量值进行编码后传输，最后将编码后的测量值传输问题建模为网络效益最大化问题，并利用拉格朗日乘数法得到近似最优解。仿真实验结果表明，该方法是有效的，在数据重构精度以及网络生命周期等方面都要优于传统的方法。