移动机器人容错的离散性

D. Pattanayak, Gokarna Sharma, P. Mandal
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引用次数: 6

摘要

图上的分散问题要求初始任意放置在n节点匿名图节点上的k≤n个机器人自主重新定位,以达到每个机器人在不同节点上的配置。该问题涉及许多基本的机器人协调问题,如探索、分散、负载平衡、自动驾驶电动汽车(机器人)向充电站(节点)的迁移等,因此引起人们的兴趣。这个问题的目标是同时最小化(或提供折衷)两个基本性能指标:(i)实现分散的时间和(ii)每个机器人所需的内存。文献在考虑无故障机器人的任意图上解决了这个问题。在本文中,我们研究了考虑崩溃故障机器人的任意图上的色散——一个机器人在崩溃后连同它所携带的信息一起从系统中消失。我们提出了一种确定性的O((min (m, kΔ)·f)时间算法,以O(log (max (k, Δ))位内存实现每个机器人从根初始配置开始的分散,使得所有k个机器人都在单个节点上,其中m是边的数量,f≤k是崩溃的数量,Δ是图的最大程度。当Δ和f都是O(1)时,我们的算法的时间复杂度渐近地匹配下界Ω(k),当Δ和f都是polylog(n)时,它是polylog(n)远离下界Ω(k)的因子。内存界是渐近最优的。据我们所知,这是任意图中带有错误的色散的第一个结果,即使从根初始配置开始也是如此。
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Dispersion of Mobile Robots Tolerating Faults
The dispersion problem on graphs asks k ≤ n robots initially placed arbitrarily on the nodes of an n-node anonymous graph to reposition autonomously to reach a configuration with each robot on a distinct node. This problem is of interest due to its relationship to many fundamental robot coordination problems, such as exploration, scattering, load balancing, relocation of self-driven electric cars (robots) to recharge stations (nodes), etc. The objective of this problem is to minimize simultaneously (or provide trade-off between) two fundamental performance metrics: (i) time to achieve dispersion and (ii) memory needed at each robot. The literature solved this problem on arbitrary graphs considering fault-free robots. In this paper, we study dispersion on arbitrary graphs considering crash faulty robots – a robot which has crashed vanishes from the system along with the information it carried. We present a deterministic O((min (m, kΔ) · f) time algorithm achieving dispersion with O(log (max (k, Δ))) bits memory at each robot starting from rooted initial configurations such that all k robots are on a single node, where m is the number of edges, f ≤ k is the number of crashes, and Δ is the maximum degree of the graph. When Δ and f are both O(1), time complexity of our algorithm asymptotically matches the lower bound Ω(k) and when Δ and f are both polylog(n), it is polylog(n) factor away from the lower bound Ω(k). The memory bound is asymptotically optimal. To the best of our knowledge, this is the first result for dispersion with faults in arbitrary graphs, even when starting from rooted initial configurations.
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