Mobile agents have emerged as a powerful framework for solving fundamental graph problems in distributed settings in recent times. These agents, modelled as autonomous physical or software entities, possess local computation power, finite memory and have the ability to traverse a graph, offering efficient solutions to a range of classical problems. In this work, we focus on the problem of computing a \emph{minimal dominating set} (mDS) in anonymous graphs using mobile agents. Building on the recently proposed optimal dispersion algorithm on the synchronous mobile agent model, we design two new algorithms that achieve a \emph{linear-time} solution for this problem in the synchronous setting. Specifically, given a connected $n$-node graph with $n$ agents initially placed in either rooted or arbitrary configurations, we show that an mDS can be computed in $O(n)$ rounds using only $O(\log n)$ bits of memory per agent, without using any prior knowledge of any global parameters. This improves upon the best-known complexity results in the literature over the same model. In addition, as natural by-products of our methodology, our algorithms also construct a spanning tree and elect a unique leader in $O(n)$ rounds, which are also important results of independent interest in the mobile-agent framework.
翻译:近年来,移动智能体已发展成为分布式环境下解决图论基础问题的强大框架。这些智能体被建模为自主的物理或软件实体,具备本地计算能力、有限存储空间以及遍历图结构的能力,为一系列经典问题提供了高效解决方案。本文聚焦于在匿名图中利用移动智能体计算最小支配集的问题。基于近期提出的同步移动智能体模型最优分散算法,我们设计了两种新算法,在同步设置下实现了该问题的线性时间求解。具体而言,给定一个连通的n节点图,其中n个智能体初始以根节点或任意配置分布,我们证明仅需每个智能体使用O(log n)比特存储空间,无需任何全局参数的先验知识,即可在O(n)轮内计算出最小支配集。该结果改进了现有文献中相同模型下的最优复杂度。此外,作为本方法的自然副产品,我们的算法还能在O(n)轮内同时构造生成树并选举唯一领导者,这些成果在移动智能体框架中同样具有独立研究价值。