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首页> 外文期刊>Networking, IEEE/ACM Transactions on >Bounding Interference in Wireless Ad Hoc Networks With Nodes in Random Position
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Bounding Interference in Wireless Ad Hoc Networks With Nodes in Random Position

机译:节点处于随机位置的无线自组织网络中的边界干扰

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摘要

Given a set of positions for wireless nodes, the interference minimization problem is to assign a transmission radius (i.e., a power level) to each node such that the resulting communication graph is connected while minimizing the maximum (respectively, average) interference. We consider the model introduced by von Rickenbach (2005), in which each wireless node is represented by a point in Euclidean space on which is centered a transmission range represented by a ball, and edges in the corresponding graph are symmetric. The problem is NP-complete in two or more dimensions (Buchin 2008), and no polynomial-time approximation algorithm is known. We show how to solve the problem efficiently in settings typical for wireless ad hoc networks. If nodes are represented by a set of points selected uniformly and independently at random over a -dimensional rectangular region, then the topology given by the closure of the Euclidean minimum spanning tree of has maximum interference with high probability and expected interference. We extend the first bound to a general class of communication graphs over a broad set of probability distributions. We present a local algorithm that constructs a graph from this class; this is the first local algorithm to provide an upper bound on expected maximum interference. Finally, we disprove a conjecture of Devroye and Morin (2012) relating the maximum interference of the Euclidean minimum spanning tree to the optimal maximum interference attainable.
机译:给定用于无线节点的一组位置,干扰最小化问题是向每个节点分配传输半径(即,功率水平),使得在最小化最大(分别为平均)干扰的同时,连接所得到的通信图。我们考虑冯·里肯巴赫(von Rickenbach,2005)引入的模型,其中每个无线节点由欧几里得空间中的一个点表示,该点以球表示的传输范围为中心,并且对应图中的边缘是对称的。问题是在两个或多个维度上都是NP完全的(Buchin 2008),并且没有多项式时间近似算法是已知的。我们展示了如何在无线ad hoc网络的典型设置中有效解决问题。如果节点由在一个二维矩形区域上随机且均匀且独立选择的一组点表示,则由的欧几里德最小生成树的闭合给出的拓扑将具有最大的干扰,并且具有较高的概率和预期的干扰。我们将第一类边界扩展到一组广泛的概率分布上的一般通信图类。我们提出了一种本地算法,该算法从该类构造图形。这是第一个提供预期最大干扰上限的本地算法。最后,我们驳斥了Devroye和Morin(2012)的推测,该推测将欧几里得最小生成树的最大干扰与可达到的最佳最大干扰联系起来。

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