Stability and Resilience of Distributed Information Spreading in Aggregate Computing

TL;DR

This paper enhances distributed information spreading algorithms in aggregate computing, making them resilient to network disturbances, with proven stability and boundedness depending on perturbation size and network diameter.

Contribution

It introduces a resilient, self-stabilizing spreading algorithm with proven stability properties and analyzes the trade-offs between resilience and convergence speed.

Findings

Algorithm is resilient to network perturbations

Global asymptotic stability is established

Boundedness depends on perturbation magnitude and network diameter

Abstract

Spreading information through a network of devices is a core activity for most distributed systems. As such, self-stabilizing algorithms implementing information spreading are one of the key building blocks enabling aggregate computing to provide resilient coordination in open complex distributed systems. This paper improves a general spreading block in the aggregate computing literature by making it resilient to network perturbations, establishes its global uniform asymptotic stability and proves that it is ultimately bounded under persistent disturbances. The ultimate bounds depend only on the magnitude of the largest perturbation and the network diameter, and three design parameters trade off competing aspects of performance. For example, as in many dynamical systems, values leading to greater resilience to network perturbations slow convergence and vice versa.