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From Sensor to Processing Networks: Optimal Estimation with Computation and Communication Latency
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1-s2.0-S2405896320304948-main.pdf
Description
Published version
Size
1.26 MB
Format
Adobe PDF
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938b24534a96c1121295d5012cc1d0da
Author(s) • •
Ballotta, Luca
Schenato, Luca
Carlone, Luca
Date Issued
2020
Journal
IFAC-PapersOnLine
Publisher
Elsevier BV
Citation
Ballotta, Luca, Schenato, Luca and Carlone, Luca. 2020. "From Sensor to Processing Networks: Optimal Estimation with Computation and Communication Latency." IFAC-PapersOnLine, 53 (2).
Version
Final published version
Abstract
This 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 of processing network. Contrarily to sensor and communication networks, where the designer is concerned with the design of a suitable communication policy, in a processing network one 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.
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Creative Commons Attribution-NonCommercial-NoDerivs License
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DOI of Published Version
10.1016/J.IFACOL.2020.12.223