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Distributed Tracking with Energy Management in Wireless Sensor Networks

机译:无线传感器网络中具有能量管理的分布式跟踪

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We consider a wireless sensor network (WSN) tasked with tracking a process using a set of distributed nodes. Here multiple remote sensor nodes estimate the physical process (viz., a moving object) and transmit quantized estimates to a fusion center for processing. At the fusion node a BLUE (best linear unbiased estimation) approach is used to combine the sensor estimates and to create a final estimate of the state. In this framework the uncertainty of the overall estimate is derived and shown to depend on the individual sensor transmit energy and quantization levels, as well as the Kalman tracker uncertainty at the node. Since power and bandwidth are critically constrained resources in battery operated sensor nodes, we attempt to quantify the trade-off between the lifetime of the network and the estimation quality over time. Three different convex formulations of the underlying nonconvex mixed integer nonlinear optimization problem are presented. Unlike previous work this effort incorporates the operating state of the nodes into the decisions of the optimum bits and the transmission power levels based on a heuristic. Simulation results for all formulations demonstrate the quality of the state estimate as well as the extended lifetime of the WSN.
机译:我们考虑一个无线传感器网络(WSN),该网络负责使用一组分布式节点来跟踪过程。在此,多个远程传感器节点估计物理过程(即运动对象),并将量化的估计值传输到融合中心进行处理。在融合节点上,使用BLUE(最佳线性无偏估计)方法来组合传感器估计并创建状态的最终估计。在此框架中,得出了总体估计的不确定性,并显示出该不确定性取决于各个传感器的发射能量和量化级别以及节点处的卡尔曼跟踪器不确定性。由于功率和带宽是电池供电的传感器节点中的关键约束资源,因此我们尝试量化网络的寿命与估算质量之间的权衡。提出了基本的非凸混合整数非线性优化问题的三种不同的凸公式。与先前的工作不同,此工作将节点的操作状态纳入基于启发式的最佳位和传输功率级别的决策中。所有配方的仿真结果均表明状态估计的质量以及WSN的延长寿命。

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