Efficient dispersion of mobile robots on graphs

A. Kshemkalyani, Faizan Ali
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引用次数: 33

Abstract

The dispersion problem on graphs requires k robots placed arbitrarily at the n nodes of an anonymous graph, where k ≤ n, to coordinate with each other to reach a final configuration in which each robot is at a distinct node of the graph. The dispersion problem is important due to its relationship to graph exploration by mobile robots, scattering on a graph, and load balancing on a graph. In addition, an intrinsic application of dispersion has been shown to be the relocation of self-driven electric cars (robots) to recharge stations (nodes). We propose five algorithms to solve dispersion on graphs. The first three algorithms require O(k log Δ) bits at each robot and O(m) steps running time, where m is the number of edges and Δ is the degree of the graph. The algorithms differ in whether they address the synchronous or the asynchronous system model, and in what, where, and how data structures are maintained. The fourth algorithm, for the asynchronous model, has a space usage of O(D log Δ) bits at each robot and uses O(ΔD) steps, where D is the graph diameter. The fifth algorithm, for the asynchronous model, has a space usage of O(max(log k, log Δ)) bits at each robot and uses O((m - n)k) steps.
移动机器人在图上的高效分散
图上的分散问题需要k个机器人任意放置在匿名图的n个节点上,k≤n,相互协调,以达到每个机器人在图的不同节点上的最终构型。分散问题是一个重要的问题,因为它与移动机器人的图探索、图上的分散和图上的负载平衡有关。此外,分散的一个内在应用已被证明是自动驾驶电动汽车(机器人)重新安置到充电站(节点)。我们提出了五种算法来解决图上的色散。前三种算法在每个机器人上需要O(k log Δ)位和O(m)步运行时间,其中m是边的数量,Δ是图的度。这些算法的不同之处在于它们处理的是同步系统模型还是异步系统模型,以及维护数据结构的内容、位置和方式。对于异步模型,第四种算法在每个机器人上的空间使用为O(D log Δ)位,并使用O(ΔD)步,其中D是图直径。对于异步模型,第五种算法在每个机器人上的空间使用为O(max(log k, log Δ))位,并使用O((m - n)k)步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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