Paper Info
Title
A Lyapunov Analysis For The Robust Stability Of An Adaptive Bellman-Ford Algorithm
Abstract
Self-stabilizing (asymptotically stable) distance estimation algorithms are an important building block of many distributed systems featuring in Spatial or Aggregate computing, but the dynamics of their convergence to correct distance estimates has not previously been formally analyzed. As a first step to understanding, how they behave in interconnections involving other building blocks, it is important to develop a Lyapunov framework to demonstrate their robust stability. This paper addresses this shortcoming by providing the first Lyapunov-based analysis of an adaptive Bellman-Ford algorithm, by formulating a simple Lyapunov function. This analysis proves global uniform asymptotic stability of such algorithms, a property which the classical Bellman-Ford algorithm lacks, thus demonstrating a measure of robustness to structural perturbations, empirically observed by us in a previous work.
Year
Venue
Field
2016
2016 IEEE 55TH CONFERENCE ON DECISION AND CONTROL (CDC)
Lyapunov function,Mathematical optimization,Control theory,Bellman–Ford algorithm,Computer science,Lyapunov optimization,Robustness (computer science),Lyapunov redesign,Adaptive control,Lyapunov exponent,Stability theory
DocType
ISSN
Citations 
Conference
0743-1546
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Soura Dasgupta167996.96
Jacob Beal29312.12