Stabilizing Tiny Interaction Protocols

TL;DR

This paper introduces a self-stabilizing approach for token-based algorithms in tiny interaction protocols, utilizing oblivious mobile agents to enhance network stabilization, and unifies models from mobile robots and population protocols.

Contribution

It presents the first model combining mobile robot and population protocol paradigms for self-stabilization in tiny interaction settings.

Findings

Oblivious stateless agents can achieve self-stabilization.

The agent paradigm is effective for stabilization in TIP.

A unified model of mobile robots and population protocols is proposed.

Abstract

In this paper we present the self-stabilizing implementation of a class of token based algorithms. In the current work we only consider interactions between weak nodes. They are uniform, they do not have unique identifiers, are static and their interactions are restricted to a subset of nodes called neighbours. While interacting, a pair of neighbouring nodes may create mobile agents (that materialize in the current work the token abstraction) that perform traversals of the network and accelerate the system stabilization. In this work we only explore the power of oblivious stateless agents. Our work shows that the agent paradigm is an elegant distributed tool for achieving self-stabilization in Tiny Interaction Protocols (TIP). Nevertheless, in order to reach the full power of classical self-stabilizing algorithms more complex classes of agents have to be considered (e.g. agents with memory, identifiers or communication skills). Interestingly, our work proposes for the first time a model that unifies the recent studies in mobile robots(agents) that evolve in a discrete space and the already established population protocols paradigm.