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A probabilistic dynamic energy model for ad-hoc wireless sensors network with varying topology.

机译：具有变化拓扑的自组织无线传感器网络的概率动态能量模型。

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摘要

In this dissertation we investigate the behavior of Wireless Sensor Networks (WSNs) from the degree distribution and evolution perspective. In specific, we focus on implementation of a scale-free degree distribution topology for energy efficient WSNs.;WSNs is an emerging technology that finds its applications in different areas such as environment monitoring, agricultural crop monitoring, forest fire monitoring, and hazardous chemical monitoring in war zones. This technology allows us to collect data without human presence or intervention. Energy conservation/efficiency is one of the major issues in prolonging the active life WSNs. Recently, many energy aware and fault tolerant topology control algorithms have been presented, but there is dearth of research focused on energy conservation/efficiency of WSNs.;Therefore, we study energy efficiency and fault-tolerance in WSNs from the degree distribution and evolution perspective. Self-organization observed in natural and biological systems has been directly linked to their degree distribution. It is widely known that scale-free distribution bestows robustness, fault-tolerance, and access efficiency to system. Fascinated by these properties, we propose two complex network theoretic self-organizing models for adaptive WSNs. In particular, we focus on adopting the Barabasi and Albert scale-free model to fit into the constraints and limitations of WSNs. We developed simulation models to conduct numerical experiments and network analysis. The main objective of studying these models is to find ways to reducing energy usage of each node and balancing the overall network energy disrupted by faulty communication among nodes.;The first model constructs the wireless sensor network relative to the degree (connectivity) and remaining energy of every individual node. We observed that it results in a scale-free network structure which has good fault tolerance properties in face of random node failures. The second model considers additional constraints on the maximum degree of each node as well as the energy consumption relative to degree changes. This gives more realistic results from a dynamical network perspective. It results in balanced network-wide energy consumption. The results show that networks constructed using the proposed approach have good properties for different centrality measures.;The outcomes of the presented research are beneficial to building WSN control models with greater self-organization properties which leads to optimal energy consumption.
机译：本文从程度分布和演化角度研究无线传感器网络的行为。具体而言，我们专注于为节能型WSN实现无标度分布拓扑； WSN是一种新兴技术，可在环境监控，农作物监控，森林火灾监控和危险化学监控等不同领域找到应用在战区。这项技术使我们无需人工参与或干预即可收集数据。节能/效率是延长无线传感器网络使用寿命的主要问题之一。近年来，提出了许多能量感知和容错的拓扑控制算法，但目前还缺乏针对无线传感器网络的节能/效率的研究。因此，我们从程度分布和演化的角度研究无线传感器网络的能效和容错。 。在自然和生物系统中观察到的自组织与它们的程度分布直接相关。众所周知，无标度分配具有鲁棒性，容错性和对系统的访问效率。着迷于这些特性，我们为自适应WSN提出了两个复杂的网络理论自组织模型。特别是，我们专注于采用Barabasi和Albert无标度模型来适应WSN的约束和局限。我们开发了仿真模型以进行数值实验和网络分析。研究这些模型的主要目的是找到减少每个节点的能量消耗并平衡由于节点之间的错误通信而中断的整体网络能量的方法。第一个模型构造相对于程度（连接性）和剩余能量的无线传感器网络。每个单独的节点。我们观察到，这导致了无标度网络结构，该结构在面对随机节点故障时具有良好的容错特性。第二个模型考虑了每个节点的最大度数以及与度数变化有关的能耗的其他约束。从动态网络的角度来看，这给出了更现实的结果。这样可以在整个网络范围内平衡能耗。结果表明，采用本文提出的方法构建的网络对于不同的集中度度量都有良好的性能。所研究的结果有利于建立具有更大自组织特性的WSN控制模型，从而实现最优的能耗。

著录项

  • 作者

    Al-Husseini, Amal.;

  • 作者单位

    Northeastern University.;

  • 授予单位 Northeastern University.;
  • 学科 Engineering General.;Engineering Electronics and Electrical.;Energy.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 146 p.
  • 总页数 146
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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