【24h】

Coordinated Consensus in Dynamic Networks

机译:动态网络中的协调达成共识

获取原文

摘要

We study several variants of coordinated consensus in dynamic networks. We assume a synchronous model, where the communication graph for each round is chosen by a worst-case adversary. The network topology is always connected, but can change completely from one round to the next. The model captures mobile and wireless networks, where communication can be unpredictable. In this setting we study the fundamental problems of eventual, simultaneous, and A-coordinated consensus, as well as their relationship to other distributed problems, such as determining the size of the network. We show that in the absence of a good initial upper bound on the size of the network, eventual consensus is as hard as computing deterministic functions of the input, e.g., the minimum or maximum of inputs to the nodes. We also give an algorithm for computing such functions that is optimal in every execution. Next, we show that simultaneous consensus can never be achieved in less than n - 1 rounds in any execution, where n is the size of the network; consequently, simultaneous consensus is as hard as computing an upper bound on the number of nodes in the network. For A-coordinated consensus, we show that if the ratio between nodes with input 0 and input 1 is bounded away from 1, it is possible to decide in time n - Θ((n△)~(1/2)), where △ bounds the time from the first decision until all nodes decide. If the dynamic graph has diameter D, the time to decide is min{O(nD/△), n - Ω(n△/D)}, even if D is not known in advance. Finally, we show that (a) there is a dynamic graph such that for every input, no node can decide before time n-O(△~(0.28)n~(0.72)); and (b) for any diameter D = O(△), there is an execution with diameter D where no node can decide before time Ω(nD/△). To our knowledge, our work constitutes the first study of △-coordinated consensus in general graphs.
机译:我们研究了动态网络中协调协商的几种变体。我们假设一个同步模型,其中每轮的通信图是由最坏情况的对手选择的。网络拓扑始终连接,但可以完全从一轮变为下一个。该模型捕获移动和无线网络,其中通信可能是不可预测的。在这种背景下,我们研究的最后,同时,和A-协调的共识,其它分布问题,如确定网络规模的根本问题,以及他们之间的关系。我们表明,在没有网络大小的良好初始上限的情况下,最终的共识是计算输入的确定性功能,例如,节点的输入的最小值或最大值。我们还提供了一种计算在每个执行中最佳的函数的算法。接下来,我们表明,在任何执行中,我们都可以在不到N - 1轮的情况下实现同时共识,其中n是网络的大小;因此,同时共识与计算网络中节点数量的上限一样努力。对于协调的共识,我们表明,如果输入0和输入1的节点之间的比率偏向1,则可以在时间n - θ((n△)〜(1/2))中决定△在所有节点决定之前绑定了第一决定的时间。如果动态图具有直径D,则即使D预先知道D,决定的时间是MIN {O(ND /∞),n - ω(n△/ d)}。最后,我们表明(a)有一个动态图,使得每次输入都没有节点可以在时间n-o之前决定(△〜(0.28)n〜(0.72)); (b)对于任何直径d = o(△),有直径d的执行,其中没有节点可以在时间ω(nd /∞)之前决定。据我们所知,我们的工作构成了第一次在一般图表中达成的协商一致的研究。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号