Efficient Dispersion of Mobile Agents without Global Knowledge

TL;DR

This paper introduces a dispersion algorithm for mobile agents in graphs that operates efficiently without requiring global knowledge, matching previous algorithms in speed and using less memory.

Contribution

The authors develop a dispersion algorithm that eliminates the need for global knowledge, maintaining asymptotic efficiency and reducing memory requirements.

Findings

Achieves dispersion without global knowledge.

Maintains similar asymptotic running time.

Uses slightly less memory than prior algorithms.

Abstract

We consider the dispersion problem for mobile agents. Initially, k agents are located at arbitrary nodes in an undirected graph. Agents can migrate from node to node via an edge in the graph synchronously. Our goal is to let the k agents be located at different k nodes with minimizing the number of steps before dispersion is completed and the working memory space used by the agents. Kshemkalyani and Ali [ICDCN, 2019] present a fast and space-efficient dispersion algorithm with the assumption that each agent has global knowledge such as the number of edges and the maximum degree of a graph. In this paper, we present a dispersion algorithm that does not require such global knowledge but keeps the asymptotically same running time and slightly smaller memory space.