How to Meet at a Node of Any Connected Graph

Subhash Bhagat, A. Pelc
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引用次数: 2

Abstract

Two mobile agents have to meet at the same node of a connected graph with unlabeled nodes. This intensely researched task is known as rendezvous. The adversary assigns the agents different starting nodes in the graph and different integer labels from a set { 1 , . . . , L } . Time is slotted in synchronous rounds. The adversary wakes up the agents in possibly different rounds. After wakeup, the agents move as follows. In each round, an agent can either stay idle or move to an adjacent node. Each agent knows its label but not the label of the other agent, and agents have no a priori information about the graph. They do not know L . They execute the same deterministic algorithm whose parameter is the agent’s label. The time of a rendezvous algorithm is the worst-case number of rounds since the wakeup of the earlier agent till the meeting. In most of the results concerning rendezvous in graphs, the graph is finite and rendezvous relies on the exploration of the entire graph. Thus the time of rendezvous depends on the size of the graph. This approach is inefficient for very large graphs, and cannot be used for infinite graphs. For such graphs it is natural to seek rendezvous algorithms whose time depends on the initial distance D between the agents. In this paper we adopt this approach and consider rendezvous in arbitrary connected graphs with nodes of finite degrees, and whose set of nodes is finite or countably infinite. Our main result is the first deterministic rendezvous algorithm working under this general scenario. For any node v and any positive integer r , let P ( v, r ) be the number of paths of length r in the graph, starting at node v . For any instance of the rendezvous problem where agents start at nodes v 1 and v 2 at distance D , let P ( v 1 , v 2 , D ) = max( P ( v 1 , D ) , P ( v 2 , D )). It is well that, in trees, Ω( D + P , v 2 , D ) + log L ) is a lower bound on rendezvous time for such an instance. The time of our algorithm, working for arbitrary connected graphs of finite degrees, is polynomial in this lower bound. As an application we solve the problem of approach for synchronous agents in terrains in the plane, in time polynomial in log L and in the initial distance between the agents in the terrain. of algorithms; of computation → Distributed algorithms
如何在任何连通图的节点上相遇
两个移动代理必须在具有未标记节点的连通图的同一节点上相遇。这一密集研究任务被称为交会。攻击者在图中为代理分配不同的起始节点,并从集合{1,…, l}。时间是按同步回合分配的。对手可能会在不同的回合中唤醒特工。唤醒后,代理按如下方式移动。在每一轮中,代理可以保持空闲状态,也可以移动到相邻的节点。每个智能体都知道自己的标签,但不知道其他智能体的标签,并且智能体没有关于图的先验信息。他们不认识L。它们执行相同的确定性算法,其参数是代理的标签。集合算法的时间是指从较早的代理被唤醒到集合的最坏情况下的轮数。在大多数关于图中会合的结果中,图是有限的,会合依赖于对整个图的探索。因此集合的时间取决于图的大小。这种方法对于非常大的图是低效的,并且不能用于无限的图。对于这样的图,很自然地寻求集合算法,其时间取决于代理之间的初始距离D。本文采用这种方法,研究了节点为有限次的任意连通图的节点集为有限或可数无限的交会问题。我们的主要结果是在这种一般情况下工作的第一个确定性会合算法。对于任意节点v和任意正整数r,设P (v, r)为图中长度为r的路径的个数,从节点v开始。对于集合问题的任何实例,其中智能体从节点v1和v2出发,距离为D,设P (v1, v2, D) = max(P (v1, D), P (v2, D))。很好,在树中,Ω(D + P, v 2, D) + log L)是这种实例的集合时间的下界。对于任意有限次的连通图,我们的算法的时间是这个下界的多项式。作为一个应用,我们用log L的时间多项式和地形中agent之间的初始距离来解决平面内地形中同步agent的逼近问题。的算法;分布式算法
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