Optimized Node Selection for Compressive Sleeping Wireless Sensor Networks
Optimized Node Selection for Compressive Sleeping Wireless Sensor Networks
复制标题
压缩休眠无线传感器网络的优化节点选择
DOI：
10.1109/tvt.2015.2400635
复制
发表时间：
2016-02-01
影响因子：
6.8
通讯作者：
Wassell, Ian J.
中科院分区：
文献类型：
--
作者：
Chen, Wei;Wassell, Ian J.
在本文中，我们提出了一个压缩睡眠无线传感器网络（WSNs）的主动节点选择框架，以提高信号采集性能，网络寿命和频谱资源的使用。虽然传统的压缩睡眠无线传感器网络只利用传感器节点的空间相关性，所提出的方法进一步利用时间相关性，通过使用在前一个时刻重建的数据的支持来选择活动节点。节点选择问题被设计成一个专门的传感矩阵，其中的传感矩阵由选定的行的单位矩阵。通过利用基因辅助重建过程，我们制定的主动节点选择问题转化为一个优化问题，然后近似的约束凸松弛加舍入方案。仿真结果表明，我们提出的主动节点选择方法，导致改善重建性能，网络寿命和频谱利用率，在压缩睡眠无线传感器网络的各种节点选择方案相比。
In this paper, we propose an active node selection framework for compressive sleeping wireless sensor networks (WSNs) to improve signal acquisition performance, network lifetime, and the use of spectrum resources. While conventional compressive sleeping WSNs only exploit the spatial correlation of sensor nodes, the proposed approach further exploits the temporal correlation by selecting active nodes using the support of the data reconstructed in the previous time instant. The node selection problem is framed as the design of a specialized sensing matrix, where the sensing matrix consists of selected rows of an identity matrix. By capitalizing on a genie-aided reconstruction procedure, we formulate the active node selection problem into an optimization problem, which is then approximated by a constrained convex relaxation plus a rounding scheme. Simulation results show that our proposed active node selection approach leads to an improved reconstruction performance, network lifetime, and spectrum usage, in comparison to various node selection schemes for compressive sleeping WSNs.