基于投影矢量的双组播树高效路由数据收集

发布时间：2018-04-14 21:58

本文选题：压缩感知 + 观测矢量　；参考：《传感技术学报》2013年04期

【摘要】：现有的节点数据收集算法复杂度高,与路由结合效果不理想,且不能满足无线传感器网络高效能量的节点数据收集,而压缩感知理论具有容错性好、编码简单的优点。基于压缩感知的特性,提出了一种传感器网络中基于投影矢量的双组播树高效路由数据收集,该算法将贝叶斯压缩感知理论与传感器路由相结合,解决现有算法不能满足传感器对能耗敏感的问题。算法的基本思想首先根据初始观测矢量来寻求能量高效并得到合适路由的最优投影。然后利用节点系数能耗最小与广义矢量的主分量作为目标节点,采用微分熵改变量最大的原则进行求解节点最佳投影系数,最后在Sink与目标节点路由问题上采用正逆向组播树进行路由构造。理论和仿真结果表明在保证能耗的条件下取得了较好的重建仿真效果,对无线传感器通信具有一定的实用价值。
[Abstract]:The existing node data collection algorithms have high complexity, poor performance in combination with routing, and can not meet the needs of node data collection with efficient energy in wireless sensor networks. Compression sensing theory has the advantages of good fault tolerance and simple coding.Based on the characteristics of compression sensing, a novel efficient routing data collection algorithm based on projection vector for dual multicast trees in sensor networks is proposed. The algorithm combines Bayesian compression sensing theory with sensor routing.To solve the problem that the existing algorithm can not satisfy the sensor's sensitivity to energy consumption.The basic idea of the algorithm is to seek energy efficiency and obtain the optimal projection of the appropriate route according to the initial observation vector.Then the minimum energy consumption of node coefficients and the principal components of generalized vectors are used as target nodes, and the principle of maximum variation of differential entropy is used to solve the optimal projection coefficients of nodes.Finally, the forward and reverse multicast tree is used to construct the routing problem between Sink and target node.The theory and simulation results show that the reconstruction simulation results can be achieved under the condition of ensuring energy consumption, and it has certain practical value for wireless sensor communication.
【作者单位】：湖南工学院计算机与信息科学学院;
【基金】：国家自然科学基金重点项目(60933009) 湖南教育厅科学研究项目(12C0655,11C0375)
【分类号】：TP393.02

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