Paper Info
Title
Robust Stability of Spreading Blocks in Aggregate Computing
Abstract
Self-stabilizing information spreading algorithms are an important building block of many distributed systems featuring in aggregate computing. The convergence dynamics of self-stabilizing information spreading, however, have not previously been characterized, except in the special case of a distance finding variant known as the Adaptive Bellman-Ford (ABF) Algorithm. As a step towards understanding the behavior of these algorithms, particularly when interconnected with other building blocks, it is important to develop a framework to demonstrate their robust stability. Thus, we analyze an extremely general information spreading algorithm of which ABF is a special case. We provide a proof of global uniform asymptotic stability, upper bound on the time to converge, and ultimate bounds on state error in face of persistent perturbations.
Year
DOI
Venue
2018
10.1109/CDC.2018.8618735
2018 IEEE Conference on Decision and Control (CDC)
Keywords
Field
DocType
robust stability,spreading blocks,aggregate computing,information spreading algorithms,distributed systems,convergence dynamics,Adaptive Bellman-Ford Algorithm,ABF,building blocks,extremely general information spreading algorithm,global uniform asymptotic stability
Convergence (routing),Mathematical optimization,Task analysis,Computer science,Upper and lower bounds,Robustness (computer science),Exponential stability,Perturbation (astronomy),Special case
Conference
ISSN
ISBN
Citations 
0743-1546
978-1-5386-1396-2
0
PageRank 
References 
Authors
0.34
11
3
Name
Order
Citations
PageRank
Yuanqiu Mo123.42
Soura Dasgupta267996.96
Jacob Beal39312.12