A Lyapunov Analysis of a Most Probable Path Finding Algorithm

Yuanqiu Mo; Soura Dasgupta; Jacob Beal

doi:10.1109/LCSYS.2021.3088260

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A Lyapunov Analysis of a Most Probable Path Finding Algorithm

Journal article

Peer reviewed

A Lyapunov Analysis of a Most Probable Path Finding Algorithm

Yuanqiu Mo, Soura Dasgupta and Jacob Beal

IEEE control systems letters, Vol.6, pp.1052-1057

2022

DOI: 10.1109/LCSYS.2021.3088260

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Abstract

Distributed information spreading algorithms are important building blocks in Aggregate Computing. We consider a special case, namely for finding a most probable path for message delivery from a set of sources to each device in a network. We formulate a Lyapunov function to prove its regional stability subject to initialization of estimated probabilities to the natural interval [0,1). We also prove that the algorithm converges in a finite time, and is ultimately bounded under persistent measurement errors. We provide tight bounds for convergence time, the ultimate bound, and the time for its attainment.

aggregate computing

Asymptotic stability

Convergence

Lyapunov function

Lyapunov methods

Perturbation methods

regional stability

Stability criteria

Task analysis

ultimate bounds

Urban areas

Details

Title: Subtitle: A Lyapunov Analysis of a Most Probable Path Finding Algorithm
Creators: Yuanqiu Mo - Westlake University
Soura Dasgupta - University of Iowa
Jacob Beal - Raytheon Technologies
Resource Type: Journal article
Publication Details: IEEE control systems letters, Vol.6, pp.1052-1057
Publisher: IEEE
DOI: 10.1109/LCSYS.2021.3088260
ISSN: 2475-1456
eISSN: 2475-1456
Grant note: HR001117C0049 / Defense Advanced Research Projects Agency (DARPA) (10.13039/100000185)
Language: English
Date published: 2022
Academic Unit: Electrical and Computer Engineering
Record Identifier: 9984197225202771

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