Abstract
We investigate the scalability of networked estimation under contention-based medium access. In our set-up, the state of a number of identical first-order linear plants are measured and transmitted over a shared medium. Each sensor transmits its readings to a supervisor node that maintains a continuous-time state estimate for the associated plant. When the medium access delay exceeds the sampling interval, measurements are discarded and replaced by more recent ones. Our analysis of the shared channel determines the probability of packet loss as a function of the sampling interval and the number of contending nodes. We compute the estimation distortion with periodically generated samples as a function of the packet loss rate and sampling interval, and derive a condition for stable estimator performance. We investigate the scalability limits of this stability as a function of the number of nodes. When stable estimation is possible, we provide a procedure that computes the sampling rate that minimizes the average estimation distortion. We reproduce the analysis of estimation performance when the sensors sample asynchronously according to independent Poisson counters.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
