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Connectivity analysis of wireless ad-hoc networks.

机译:无线自组织网络的连通性分析。

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摘要

Connectivity is one of the most fundamental properties of wireless ad-hoc networks as most network functions are predicated upon the network being connected. Although increasing node transmission power will improve network connectivity, too large a power level is not feasible as energy is a scarce resource in wireless ad-hoc networks. Thus, it is crucial to identify the minimum node transmission power that will ensure network connectivity with high probability.;It is known that there exists a critical level transmission power such that a suitably larger power will ensure network connectivity with high probability. A small variation across this threshold level will lead to a sharp transition of the probability that the network is connected. Thus, in order to precisely estimate the minimum node transmission power, not only do we need to identify this critical threshold, but also how fast this transition takes place. To characterize the sharpness of transition, we define weak, strong and very strong critical thresholds associated with increasing transition speeds.;In this dissertation, we seek to estimate the minimum node transmission power for large scale one-dimensional wireless ad-hoc networks under the Geometric Random Graph (GRG) models. Unlike in previous works where nodes are taken to be uniformly distributed, we assume a more general node distribution. Using the methods of first and second moments, we theoretically prove the existence of a very strong critical threshold when the density function is everywhere positive. On the other hand, only weak thresholds are shown to exist when the density function contains vanishing densities.;We also study the connectivity of two-dimensional wireless ad-hoc networks under the random connection model, which accounts for statistical channel variations. With the help of the Stein-Chen method, we derive a closed form formula for the limiting probability that there are no isolated nodes under a very general assumption of channel variations. The node transmission power to ensure the absence of isolated nodes provides a tight lower bound on the transmission power needed to ensure network connectivity.
机译:连接性是无线自组织网络的最基本属性之一,因为大多数网络功能取决于连接的网络。尽管增加节点传输功率将改善网络连接性,但是太大的功率水平是不可行的,因为能量是无线自组织网络中的稀缺资源。因此,至关重要的是确定最小的节点传输功率,以确保高概率地确保网络连接。众所周知,存在临界水平的传输功率,使得适当较大的功率将确保高概率地确保网络连接。跨此阈值水平的微小变化将导致网络连接概率的急剧变化。因此,为了精确地估计最小节点传输功率,我们不仅需要识别该临界阈值,而且还需要识别这种转变发生的速度。为了描述过渡的锐度,我们定义了与过渡速度增加相关的弱,强和非常强的临界阈值。本文旨在估计在网络下大规模一维无线自组织网络的最小节点传输功率。几何随机图(GRG)模型。与先前的研究中节点被认为是均匀分布的不同,我们假设节点分布更一般。使用第一矩和第二矩的方法,我们从理论上证明了当密度函数处处为正时,存在非常强的临界阈值。另一方面,当密度函数包含消失的密度时,仅显示弱阈值。;我们还研究了随机连接模型下二维无线自组织网络的连通性,这说明了统计信道的变化。借助Stein-Chen方法,我们得出了一个封闭形式的公式,用于在非常一般的信道变化假设下没有孤立节点的极限概率。确保没有孤立节点的节点传输功率为确保网络连接所需的传输功率提供了严格的下限。

著录项

  • 作者

    Han, Guang.;

  • 作者单位

    University of Maryland, College Park.;

  • 授予单位 University of Maryland, College Park.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2007
  • 页码 181 p.
  • 总页数 181
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 无线电电子学、电信技术;
  • 关键词

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