文章基本信息

标题：From Sensor to Processing Networks: Optimal Estimation with Computation and Communication Latency ⁎
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作者：Luca Ballotta ; Luca Schenato ; Luca Carlone 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2020
卷号：53
期号：2
页码：11024-11031
DOI：10.1016/j.ifacol.2020.12.223
语种：English
出版社：Elsevier
摘要：AbstractThis paper investigates the use of a networked system(e.g.,swarm of robots, smart grid, sensor network) to monitor a time-varying phenomenon of interest in the presence of communication and computation latency. Recent advances in edge computing have enabled processing to be spread across the network, hence we investigate the fundamental communication-computation trade-off, arising when a sensor has to decide whether to transmit raw data (incurring communication delay) or preprocess them (incurring computational delay) in order to compute an accurate estimate of the state of the phenomenon of interest. We propose two key contributions. First, we formalize the notion ofprocessing network.Contrarily tosensor and communication networks,where the designer is concerned with the design of a suitable communication policy, in aprocessing networkone can also control when and where the computation occurs in the network. The second contribution is to provide analytical results on the optimal preprocessing delay(i.e.,the optimal time spent on computations at each sensor) for the case with a single sensor and multiple homogeneous sensors. Numerical results substantiate our claims that accounting for computation latencies (both at sensor and estimator side) and communication delays can largely impact the estimation accuracy.
关键词：KeywordsNetworked systemscommunication latencyprocessing latencyprocessing networkresource allocationsensor fusionedge computingsmart sensors