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arXiv 2207.06243cs.DC
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动态网络中的自稳定时钟同步

Self-Stabilizing Clock Synchronization in Dynamic Networks

Bernadette Charron-Bost, Louis Penet de Monterno

摘要:

我们认为在一个同步的多智能体系统的时钟同步的基本问题。每个代理持有一个具有任意初始值的时钟,并且时钟最终必须指示相同的值。以前的算法工作在静态网络与激烈的连接属性,并假设全球信息是在每个代理。在本文中,我们提出了不同的解决方案,时变拓扑结构,既不需要强连接,也不需要任何全球知识的网络。首先,我们研究了无界时钟的情况下,并提出了一个自稳定的$MinMax$算法,如果在每个足够长的时间,但有界的时间段,有一个代理,称为根,可以发送消息,可能间接地,所有其他代理。这样的网络是高度动态的,因为根可以随时间任意变化。此外,实现这种生根性质所需的时间的界限是未知的代理。然后,我们提出了一个有限状态算法,在有限的时间周期内强连接的动态网络中的周期时钟。在这里,实现强连通性的时间界限也存在,但不应该是已知的。有趣的是,我们的算法统一了以前提出的几个看似不同的静态网络算法。接下来,我们证明了强连通性实际上是不需要的:当网络只是在有限的时间段内扎根时,我们的算法仍然有效,其中一组根变得稳定。最后,我们研究了我们的算法的时间和空间复杂度,并讨论了如何初始定时信息允许更有效的解决方案。

英文摘要:

We consider the fundamental problem of clock synchronization in a synchronous multi-agent system. Each agent holds a clock with an arbitrary initial value, and clocks must eventually indicate the same value. Previous algorithms worked in static networks with drastic connectivity properties and assumed that global information is available at each agent. In this paper, we propose different solutions for time-varying topologies that require neither strong connectivity nor any global knowledge on the network. First, we study the case of unbounded clocks, and propose a self-stabilizing $MinMax$ algorithm that works if, in each sufficiently long but bounded period of time, there is an agent, called a root, that can send messages, possibly indirectly, to all other agents. Such networks are highly dynamic in the sense that roots may change arbitrarily over time. Moreover, the bound on the time required for achieving this rootedness property is unknown to the agents. Then we present a finite-state algorithm that synchronizes periodic clocks in dynamic networks that are strongly connected over bounded period of time. Here also, the bound on the time for achieving strong connectivity exists, but is not supposed to be known. Interestingly, our algorithm unifies several seemingly different algorithms proposed previously for static networks. Next, we show that strong connectivity is actually not required: our algorithm still works when the network is just rooted over bounded period of time with a set of roots that becomes stable. Finally, we study the time and space complexities of our algorithms, and discuss how initial timing information allows for more efficient solutions.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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