动态图上移动机器人的高效分散

A. Kshemkalyani, A. R. Molla, Gokarna Sharma
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引用次数: 9

摘要

图上的分散问题要求初始任意放置在n节点匿名图的节点上的k≤n个机器人自主重新定位,以达到每个机器人在图的不同节点上的配置。这个问题非常有趣,因为它与其他基本的机器人协调问题有关,例如自动驾驶电动汽车(机器人)的探索、分散、负载平衡以及向充电站(节点)的搬迁。目标是同时最小化(或提供权衡)两个基本性能指标:(i)实现分散的时间和(ii)每个机器人的内存需求。这个问题已经在静态图上得到了比较充分的研究。本文首次在动态图上研究了这一问题。特别是,我们表明,即使每个机器人具有无限的内存和1邻域知识,在局部通信模型中,动态图上的分散是不可能解决的,其中机器人只能与存在于同一节点的其他机器人通信。然后,我们证明,即使每个机器人具有无限的内存,但没有1邻域知识,在全局通信模型中,分散是不可能解决的,其中机器人可以与图中可能位于不同节点的任何其他机器人通信。然后,我们考虑具有1邻域知识的全局通信模型,并在每个机器人具有Θ(log k)位内存的任意n节点任意匿名动态图中求解色散的时间复杂度上建立了Θ(k)的紧界。最后,我们将无故障算法扩展到具有1邻域知识的全局模型下求解(碰撞)故障机器人的离散问题。
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Efficient Dispersion of Mobile Robots on Dynamic Graphs
The dispersion problem on graphs asks k ≤n robots placed initially arbitrarily on the nodes of an n-node anonymous graph to reposition autonomously to reach a configuration in which each robot is on a distinct node of the graph. This problem is of significant interest due to its relationship to other fundamental robot coordination problems, such as exploration, scattering, load balancing, and relocation of self-driving electric cars (robots) to recharge stations (nodes). The objective is to simultaneously minimize (or provide trade-off between) two fundamental performance metrics: (i) time to achieve dispersion and (ii) memory requirement at each robot. This problem has been relatively well-studied on static graphs. In this paper, we investigate it for the very first time on dynamic graphs. Particularly, we show that, even with unlimited memory at each robot and 1-neighborhood knowledge, dispersion is impossible to solve on dynamic graphs in the local communication model, where a robot can only communicate with other robots that are present at the same node. We then show that, even with unlimited memory at each robot but without 1-neighborhood knowledge, dispersion is impossible to solve in the global communication model, where a robot can communicate with any other robot in the graph possibly at different nodes. We then consider the global communication model with 1-neighborhood knowledge and establish a tight bound of Θ(k) on the time complexity of solving dispersion in any n-node arbitrary anonymous dynamic graph with Θ(log k) bits memory at each robot. Finally, we extend the fault-free algorithm to solve dispersion for (crash) faulty robots under the global model with 1-neighborhood knowledge.
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