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Networked estimation under contention-based medium access

机译:基于竞争的媒体访问下的网络估计

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This paper studies networked estimation over a communication channel shared by a contention-based medium access protocol.A collection of N identical and physically decoupled scalar systems are sampled without sensor noise and transmitted overa common channel, using a contention-based medium access mechanism. We first carry out a calculation of the averagedistortion in estimation with irregular samples. Given the rate of packet generation at sensors, we characterize the trafficcharacteristics of the some contention-based MAC schemes. This lets us derive the statistics of inter-arrival times which inturn allows us to compute the packet loss rates and also the statistics of delay within a sample period. Using these results,we track the estimation performance as the sample generation rate and the number of contending nodes are varied. Weprovide a heuristic rule-of-thumb for choosing the sampling interval which minimizes the average distortion. By combiningthe network traffic characterization with that of the estimation performance, we show this rule performs pretty well. Carryingalong the same lines, we are able to compute the scaling limits of estimation performance with respect to the number ofcontending nodes.
机译:本文研究了基于竞争的媒体访问协议共享的通信信道上的网络估计。使用基于竞争的媒体访问机制,对N个完全相同且物理上解耦的标量系统进行采样,并且没有传感器噪声,并通过公共信道进行传输。我们首先对不规则样本的估计中的平均失真进行计算。给定传感器的数据包生成速率,我们表征了一些基于竞争的MAC方案的流量特性。这使我们能够得出到达间隔时间的统计信息,从而使我们能够计算丢包率以及采样周期内的延迟统计信息。使用这些结果,随着样本生成速率和竞争节点数量的变化,我们跟踪估计性能。我们提供了一种启发式经验法则,用于选择采样间隔,以最大程度地减少平均失真。通过将网络流量表征与估计性能相结合,我们证明了该规则的性能很好。沿着同一行,我们能够计算竞争性能相对于竞争节点数的缩放极限。

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