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In-network computation in wireless sensor networks.

机译:无线传感器网络中的网络内计算。

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摘要

Wireless sensor networks are networks of devices which collaborate to perform distributed sensing, processing, and possibly even actuation tasks. This thesis is a study of distributed tasks which require in-network communication and processing.; First, we study how distributed computation can be efficiently carried out over wireless networks. We formulate the problem as one of determining the optimal rate or frequency at which symmetric functions of data distributed throughout the network can be computed at a collection center. Under a deterministic framework and packet collision-based model, we derive scaling laws with respect to network size which characterize the maximum achievable computational throughput for different subclasses of symmetric functions over connectivity graphs of different topologies. The results indicate that the maximum rate can be exponentially higher in a multihop network in comparison to a single hop network, due to the ability to compress data in-network. There is also an exponential increase in the maximum computational throughput for type-sensitive functions in comparison to type-threshold functions, which are subclasses of symmetric functions that include most statistical functions of interest.; Next, we study another important metric in sensor networks, which is network lifetime. We consider a formulation of maximizing network lifetime given the simple task of downloading different quantities of data over nodes with different energy levels. We reduce the problem of choosing lifetime optimal routes to a linear program, and derive closed form solutions for some simple regular network topologies. In the final part of the thesis, we consider the problem of clock synchronization over multihop networks, which is a specific instance of a network task requiring distributed computation. We analyze a clock synchronization approach which leads to a distributed vector estimation problem based on noisy estimates of clock differences of pairs of nodes which can directly exchange packets. We establish connections between the error variance of optimal least-squares clock synchronization and resistances in electrical networks. We propose and analyze the convergence time of a distributed iterative algorithm to compute the optimal estimates. We also propose ways of exploiting the network connectivity graph structure in order to speed up computation.
机译:无线传感器网络是协作执行分布式传感,处理甚至可能执行任务的设备网络。本文是对需要网络内通信和处理的分布式任务的研究。首先,我们研究如何在无线网络上有效地进行分布式计算。我们将此问题公式化为确定可以在收集中心计算分布在整个网络中的数据对称函数的最佳速率或频率之一。在确定性框架和基于数据包冲突的模型下,我们针对网络大小推导了缩放定律,该定律描述了不同拓扑的连通性图上对称函数的不同子类的最大可实现计算吞吐量。结果表明,由于具有在网络中压缩数据的能力,因此与单跳网络相比,多跳网络中的最大速率可以成倍提高。与类型阈值函数相比,类型敏感函数的最大计算吞吐量也呈指数增长,类型阈值函数是对称函数的子类,其中对称函数包括大多数感兴趣的统计函数。接下来,我们研究传感器网络中的另一个重要指标,即网络寿命。考虑到在具有不同能级的节点上下载不同数量的数据这一简单任务,我们考虑了最大化网络寿命的方法。我们减少了为线性程序选择生命周期最佳路由的问题,并为某些简单的常规网络拓扑派生了封闭式解决方案。在论文的最后部分,我们考虑了多跳网络上的时钟同步问题,这是需要分布式计算的网络任务的特定实例。我们分析了一种时钟同步方法,该方法基于可直接交换数据包的成对节点的时钟差的噪声估计,导致了分布式矢量估计问题。我们在最佳最小二乘时钟同步的误差方差与电网中的电阻之间建立连接。我们提出并分析了分布式迭代算法的收敛时间,以计算最优估计。我们还提出了利用网络连接图结构以加快计算速度的方法。

著录项

  • 作者

    Giridhar, Arvind G.;

  • 作者单位

    University of Illinois at Urbana-Champaign.;

  • 授予单位 University of Illinois at Urbana-Champaign.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2006
  • 页码 100 p.
  • 总页数 100
  • 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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