图中移动机器人的自镇定
On the Self-stabilization of Mobile Robots in Graphs
摘要：
自稳定是一种通用的技术，以抵御任何瞬态故障在分布式系统。移动机器人（或代理）是分布式计算的新兴趋势之一，因为他们模仿自主的生物实体。本文的贡献有三个方面。首先，我们提出了一个新的模型，研究移动实体在网络中的瞬态故障。我们的模型不同于经典的机器人模型，因为机器人有限制的路径，他们被允许遵循，并从经典的代理模型，因为代理的数量在整个协议的执行保持固定。其次，在这个模型中，我们研究了设计自稳定算法的可能性时，这些算法运行的移动机器人（或代理）在图上进化。我们专注于机器人和代理问题的核心构建块：命名和领导者选举。毫不奇怪，当网络图拓扑和本地执行模型没有约束时，这两个问题都不可能解决。最后，使用最小的假设不可能的结果，我们提供了确定性和概率的解决方案，这两个问题，并显示这些问题的等价性的算法减少机制。
英文摘要：
Self-stabilization is a versatile technique to withstand any transient fault in a distributed system. Mobile robots (or agents) are one of the emerging trends in distributed computing as they mimic autonomous biologic entities. The contribution of this paper is threefold. First, we present a new model for studying mobile entities in networks subject to transient faults. Our model differs from the classical robot model because robots have constraints about the paths they are allowed to follow, and from the classical agent model because the number of agents remains fixed throughout the execution of the protocol. Second, in this model, we study the possibility of designing self-stabilizing algorithms when those algorithms are run by mobile robots (or agents) evolving on a graph. We concentrate on the core building blocks of robot and agents problems: naming and leader election. Not surprisingly, when no constraints are given on the network graph topology and local execution model, both problems are impossible to solve. Finally, using minimal hypothesis with respect to impossibility results, we provide deterministic and probabilistic solutions to both problems, and show equivalence of these problems by an algorithmic reduction mechanism.
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