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Structuring Unreliable Radio Networks

机译:构建不可靠的无线电网络

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In this paper we study the problem of building a connected dominating set with constant degree (CCDS) in the dual graph radio network model [4.9,10]. This model includes two types of links: reliable, which always deliver messages, and unreliable, which sometimes fail to deliver messages. Real networks compensate for this differing quality by deploying low-layer detection protocols to filter unreliable from reliable links. With this in mind, we begin by presenting an algorithm that solves the CCDS problem in the dual graph model under the assumption that every process u is provided a local link detector set consisting of every neighbor connected to u by a reliable link. The algorithm solves the CCDS problem in O((△ log~2 n)/b + log~3 n) rounds, with high probability, where △ is the maximum degree in the reliable link graph, n is the network size, and b is an upper bound in bits on the message size. The algorithm works by first building a Maximal Independent Set (MIS) in log~3 n time, and then leveraging the local topology knowledge to efficiently connect nearby MIS processes. A natural follow up question is whether the link detector must be perfectly reliable to solve the CCDS problem. With this in mind, we first describe an algorithm that builds a CCDS in O(△poly log(n)) time under the assumption of O(1) unreliable links included in each link detector set. We then prove this algorithm to be (almost) tight by showing that the possible inclusion of only a single unreliable link in each process's local link detector set is sufficient to require Ω(△) rounds to solve the CCDS problem, regardless of message size. We conclude by discussing how to apply our algorithm in the setting where the topology of reliable and unreliable links can change over time.
机译:在本文中,我们研究了在双图无线电网络模型[4.9,10]中建立具有恒定度的连通控制集(CCDS)的问题。此模型包括两种类型的链接:可靠的(始终传递消息)和不可靠的(有时无法传递消息)。实际网络通过部署低层检测协议来过滤来自可靠链路的不可靠内容,从而弥补了这种不同的质量。考虑到这一点,我们假设在每个进程u提供​​一个本地链路检测器集的情况下,提出一种解决双图模型中CCDS问题的算法,该本地链路检测器集包含通过可靠链路连接到u的每个邻居。该算法以高概率解决了O((△log〜2 n)/ b + log〜3 n)回合中的CCDS问题,其中△是可靠链路图中的最大度,n是网络规模,b是消息大小的位的上限。该算法的工作方式是首先在log〜3 n的时间内建立一个最大独立集(MIS),然后利用本地拓扑知识有效地连接附近的MIS进程。一个自然的跟进问题是链路检测器是否必须完全可靠才能解决CCDS问题。考虑到这一点,我们首先描述一种算法,该算法在每个链路检测器集中包含O(1)个不可靠链路的假设下,在O(△poly log(n))时间内构建一个CCDS。然后,我们通过证明在每个进程的本地链路检测器集中仅包含一个不可靠的链路就足以要求Ω(△)轮来解决CCDS问题,而与消息大小无关,从而证明该算法是(几乎)严格的。通过讨论如何在可靠和不可靠链接的拓扑可能随时间变化的环境中应用我们的算法而得出结论。

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