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Biologically inspired algorithms for wireless sensor networks .

机译:生物启发的无线传感器网络算法。

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摘要

In recent years, several models introduced in mathematical biology and natural science have been used as the foundation of networking primitives. These bioinspired algorithms often solve complex problems by means of simple and iterative local rules. In this work, we consider the design and development of novel decentralized algorithms for distributed systems, with applications to wireless sensor networks, wireless body area networks and formation control.We consider two models of interaction. In one model, nodes communicate via pulses whose arrival time is sensed and compared to a local state variable and triggers an appropriate local update. In the second model, the nodes can exchange integer valued messages, which we call colors.The first class of algorithms falls in the class of Pulse-Coupled Oscillator (PCO) models that were first introduced in mathematical biology and that have been recently introduced in the sensor networking area. This thesis is concerned with the design and analysis of PCO based protocols for synchronization and multiple access.The second class of protocols relates to the so called voting models introduced in Physics. The protocol was proposed for network control in particularly harsh media, where communications are severely limited by the significant distortion and delay of the link.
机译:近年来,数学生物学和自然科学中引入的几种模型已用作网络原语的基础。这些受生物启发的算法通常通过简单且迭代的局部规则来解决复杂的问题。在这项工作中,我们考虑了针对分布式系统的新型分散算法的设计和开发,并将其应用于无线传感器网络,无线人体局域网和编队控制。我们考虑了两种交互模型。在一个模型中,节点通过脉冲进行通信,这些脉冲的到达时间被感知并与本地状态变量进行比较,并触发适当的本地更新。在第二个模型中,节点可以交换整数值的消息,我们称其为颜色。第一类算法属于在数学生物学中首次引入并且最近在2000年引入的脉冲耦合振荡器(PCO)模型。传感器网络区域。本文涉及基于PCO的同步和多址访问协议的设计和分析。第二类协议涉及物理中引入的所谓的投票模型。该协议被提议用于特别苛刻的媒体中的网络控制,在这些媒体中,通信受到链接的严重失真和延迟的严重限制。

著录项

  • 作者

    Pagliari, Roberto.;

  • 作者单位

    Cornell University.;

  • 授予单位 Cornell University.;
  • 学科 Engineering Electronics and Electrical.Computer Science.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 168 p.
  • 总页数 168
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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