A Lyapunov Analysis of a Most Probable Path Finding Algorithm

被引:0
作者
Mo, Yuanqiu [1 ]
Dasgupta, Soura [2 ,3 ]
Beal, Jacob [4 ]
机构
[1] Westlake Univ, Westlake Inst Adv Study, Inst Adv Technol, Hangzhou 310024, Peoples R China
[2] Univ Iowa, Dept Elect & Comp Engn, Iowa City, IA 52242 USA
[3] Shandong Acad Sci, Shandong Comp Sci Ctr, Jinan 250014, Peoples R China
[4] Raytheon BBN Technol, Dept Informat & Knowledge Technol, Cambridge, MA 02138 USA
来源
IEEE CONTROL SYSTEMS LETTERS | 2022年 / 6卷
关键词
Lyapunov methods; Convergence; Perturbation methods; Asymptotic stability; Urban areas; Task analysis; Stability criteria; Lyapunov function; regional stability; aggregate computing; ultimate bounds;
D O I
10.1109/LCSYS.2021.3088260
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:1052 / 1057
页数:6
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