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首页> 外文期刊>Parallel and Distributed Systems, IEEE Transactions on >In-Network Estimation with Delay Constraints in Wireless Sensor Networks
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In-Network Estimation with Delay Constraints in Wireless Sensor Networks

机译:无线传感器网络中具有延迟约束的网络内估计

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The use of wireless sensor networks (WSNs) for closing the loops between the cyberspace and the physical processes is more attractive and promising for future control systems. For some real-time control applications, controllers need to accurately estimate the process state within rigid delay constraints. In this paper, we propose a novel in-network estimation approach for state estimation with delay constraints in multihop WSNs. For accurately estimating a process state as well as satisfying rigid delay constraints, we address the problem through jointly designing in-network estimation operations and an aggregation scheduling algorithm. Our in-network estimation operation performed at relays not only optimally fuses the estimates obtained from the different sensors but also predicts the upper stream sensors' estimates which cannot be aggregated to the sink before deadlines. Our estimate aggregation scheduling algorithm, which is interference free, is able to aggregate as much estimate information as possible from the network to the sink within delay constraints. We proved the unbiasedness of in-network estimation, and theoretically analyzed the optimality of our approach. Our simulation results corroborate our theoretical results and show that our in-network estimation approach can obtain significant estimation accuracy gain under different network settings.
机译:使用无线传感器网络(WSN)来封闭网络空间与物理过程之间的环路,对于将来的控制系统来说更有吸引力,而且很有希望。对于某些实时控制应用,控制器需要在严格的延迟约束范围内准确估算过程状态。在本文中,我们提出了一种新的网络内估计方法,用于在多跳WSN中具有延迟约束的状态估计。为了准确估计过程状态并满足严格的延迟约束,我们通过联合设计网络内估计操作和聚合调度算法来解决该问题。我们在中继器上进行的网络内估计操作不仅可以最佳地融合从不同传感器获得的估计值,而且可以预测上游传感器的估计值,这些估计值不能在截止日期之前汇总到接收器中。我们的估计聚合调度算法是无干扰的,能够在延迟约束范围内聚合从网络到接收器的尽可能多的估计信息。我们证明了网络内估计的无偏性,并从理论上分析了我们方法的最优性。我们的仿真结果证实了我们的理论结果,并表明我们的网络内估计方法可以在不同的网络设置下获得显着的估计精度增益。

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