论文标题
动态网络中的自动化时钟同步
Self-Stabilizing Clock Synchronization in Dynamic Networks
论文作者
论文摘要
我们考虑了同步多代理系统中时钟同步的基本问题。每个代理都保持一个任意初始值的时钟,并且时钟最终必须指示相同的值。以前的算法在具有急剧连接属性的静态网络中工作,并假设每个代理都可以使用全局信息。在本文中,我们为不需要牢固的连接性和网络上任何全球知识的时变拓扑提出了不同的解决方案。 首先,我们研究了无界时钟的情况,并提出了一种自动化的$ minmax $算法,如果在每个足够长但有限的时间段内,都有一个称为root的代理,可以间接向所有其他代理发送消息。这种网络具有高度动态的,因为根可能会随着时间的推移任意变化。此外,代理人未知实现此根源特性所需的时间的界限。然后,我们提出了一种有限状态算法,该算法同步了在有限的时间段内紧密连接的动态网络中的周期性时钟。同样,存在实现牢固连通性的时间的界限,但不应该知道。有趣的是,我们的算法统一了以前针对静态网络提出的几种看似不同的算法。接下来,我们表明不需要强大的连接:当网络只是在有限的时间内植根于一组稳定的根部时,我们的算法仍然有效。最后,我们研究算法的时间和空间复杂性,并讨论最初的时序信息如何允许更有效的解决方案。
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.