Conference proceeding
Robust Stability of Spreading Blocks in Aggregate Computing
2018 IEEE Conference on Decision and Control (CDC), Vol.2018-, pp.6007-6012
12/2018
DOI: 10.1109/CDC.2018.8618735
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.
Details
- Title: Subtitle
- Robust Stability of Spreading Blocks in Aggregate Computing
- Creators
- Yuanqiu Mo - University of IowaSoura Dasgupta - University of IowaJacob Beal - Raytheon Technologies
- Resource Type
- Conference proceeding
- Publication Details
- 2018 IEEE Conference on Decision and Control (CDC), Vol.2018-, pp.6007-6012
- Publisher
- IEEE
- DOI
- 10.1109/CDC.2018.8618735
- ISSN
- 0743-1546
- eISSN
- 2576-2370
- Language
- English
- Date published
- 12/2018
- Academic Unit
- Electrical and Computer Engineering
- Record Identifier
- 9984197339802771
Metrics
6 Record Views