能量有效的无线传感器网络.doc
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能量有效的无线传感器网络,摘 要无线传感器网络是由大量分布在监测区域内的能量有限的，并具有感知、计算和通信能力的微型传感器节点，通过自组织的方式所组成的网络。在具体应用之前，必须根据特定的应用环境准则，确定传感器节点的部署方案。覆盖作为无线传感器网络中的一个基本问题，就是保证在一定服务质量的前提下，如何实现网络覆盖范围的最大化，以提供可靠的监测...
内容介绍
此文档由会员 违规屏蔽12 发布
摘 要
无线传感器网络是由大量分布在监测区域内的能量有限的，并具有感知、计算和通信能力的微型传感器节点，通过自组织的方式所组成的网络。在具体应用之前，必须根据特定的应用环境准则，确定传感器节点的部署方案。覆盖作为无线传感器网络中的一个基本问题，就是保证在一定服务质量的前提下，如何实现网络覆盖范围的最大化，以提供可靠的监测服务。
本文主要在覆盖问题基础上，考虑节点的能量有效性，讨论研究能量有效的无线传感器网络覆盖优化。本文的主要研究工作如下：
1. 能耗均衡的覆盖策略
针对随机高密度节点布设所导致的节点覆盖区域重叠、网络能耗过大和通信冲突等问题，在选取最优覆盖节点集合的基础上，同时考虑网络区域能耗的均衡问题，研究了一种基于遗传算法的能耗均衡覆盖策略。构建概率感知模型网络，定义一个能耗均衡系数用以表示网络能耗均衡程度，以覆盖率、工作节点数和网络能耗均衡系数为优化目标，然后利用遗传算法进行求解，得到最优网络覆盖。仿真结果表明，该覆盖控制策略能够在达到较高覆盖率的同时，有效降低能耗并保证网络能量均衡，从而保持网络稳定运行和延长网络生存时间。
2. 节能的移动节点覆盖优化
针对基本粒子群算法在求解移动节点覆盖优化问题时容易陷入早熟收敛的不足，研究了基于扰动因子的粒子群覆盖优化，该方法将扰动因子融入到粒子群算法的速度更新公式中，通过扰动粒子速度指导粒子进化；另外，将量子理论和粒子群算法相结合，研究了基于量子粒子群算法覆盖优化，该方法利用量子空间中粒子满足集聚态性质完全不同的特点，在整个可行空间内进行搜索，避免了粒子群算法容易陷入局部最优的问题。结果表明，两种改进算法均能改善网络覆盖性能，并且量子粒子群方法可以减少平均移动距离，达到节能覆盖的目的。
关键词 无线传感器网络；覆盖优化；能量有效；遗传算法；粒子群算法
Abstract
Wireless sensor network is composed of a large number of energy limited micro-sensor nodes distributed in the monitoring regions, which have the sensing, computing and communicating capabilities through self-organized manner. Before the specific applications, the methods of deploying the sensor nodes should be determined according to the criteria of application-specific environments. As one of the fundamental problems in the wireless sensor network, the researches of coverage focus on the case that how to maximize the coverage regions and achieve the reliable area observation with quality of service.
Based on the problem of coverage, with the consideration of energy efficiency, this paper discusses and researches energy efficient coverage optimization of wireless sensor network. The main research works are as follows:
1. Energy-balanced coverage strategy
To solve the problems of coverage overlap、excessive energy consumption and communication conflicts caused by deploying nodes with high density, based on the selection of the optimal coverage set of nodes, an energy-balanced coverage strategy is researched. A network of probabilistic sensing model is built and an energy balance coefficient is set. Network coverage, working nodes and energy consumption coefficient are the optimization goals, then the genetic algorithm is used to get the optimal coverage solution. Simulation results show that the strategy can reduce and balance the energy consumption while ensuring the high network coverage, thus making the network work stably and prolonging the network lifetime efficiently.
2. Energy-efficient coverage optimization of dynamic nodes
When used to solve the coverage optimization problem of dynamic nodes, PSO easily falls into the local optimum. So the coverage optimization based on disturbance-factor PSO is researched. The strategy adds a disturbance factor to the updating formula of PSO, thus guiding the evolution; Then, with the combination of quantum theory and PSO, the coverage optimization based on QPSO is researched. The aggregation characteristic of every particle in the quantum space is unique, so the algorithm can search throughout the entire feasible region. Thus the QPSO, of which global search ability is much better than PSO, can avoid the disadvantages of being easily trapped into a local extreme. Simulation results show that the proposed algorithms are better than PSO in coverage optimization and the algorithm based on QPSO can eliminate the mean moving distance of the nodes, thus meeting the aim of energy-efficient coverage.
Key words wireless sensor networks; coverage optimization; energy efficient; genetic algorithm; particle swarm optimization algorithm
目 录
摘 要 I
Abstract III
第1章 绪论 1
1.1 研究背景 1
1.1.1 无线传感器网络简介 1
1.1.2 无线传感器网络的特点 3
1.1.3 无线传感器网络的关键技术 4
1.1.4 无线传感器网络的研究现状与应用 5
1.2 课题研究目的和意义 5
1.3 本文的主要工作 6
1.4 本文的组织结构 7
第2章 无线传感器网络覆盖问题 9
2.1 引言 9
2.2 无线传感器网络覆盖分类 9
2.3 典型的覆盖算法分析 12
2.3.1 基于静态节点调度的覆盖算法 12
2.3.2 基于移动节点的覆盖算法 14
2.4 覆盖性能指标 16
2.5 覆盖算法评价标准 18
2.6 本章小结 19
第3章 基于遗传算法的能耗均衡覆盖策略 21
3.1 问题概述 21
3.1.1 传感器节点覆盖模型 22
3.1.2 网络覆盖模型 24
3.2 遗传算法原理 24
3.2..
无线传感器网络是由大量分布在监测区域内的能量有限的，并具有感知、计算和通信能力的微型传感器节点，通过自组织的方式所组成的网络。在具体应用之前，必须根据特定的应用环境准则，确定传感器节点的部署方案。覆盖作为无线传感器网络中的一个基本问题，就是保证在一定服务质量的前提下，如何实现网络覆盖范围的最大化，以提供可靠的监测服务。
本文主要在覆盖问题基础上，考虑节点的能量有效性，讨论研究能量有效的无线传感器网络覆盖优化。本文的主要研究工作如下：
1. 能耗均衡的覆盖策略
针对随机高密度节点布设所导致的节点覆盖区域重叠、网络能耗过大和通信冲突等问题，在选取最优覆盖节点集合的基础上，同时考虑网络区域能耗的均衡问题，研究了一种基于遗传算法的能耗均衡覆盖策略。构建概率感知模型网络，定义一个能耗均衡系数用以表示网络能耗均衡程度，以覆盖率、工作节点数和网络能耗均衡系数为优化目标，然后利用遗传算法进行求解，得到最优网络覆盖。仿真结果表明，该覆盖控制策略能够在达到较高覆盖率的同时，有效降低能耗并保证网络能量均衡，从而保持网络稳定运行和延长网络生存时间。
2. 节能的移动节点覆盖优化
针对基本粒子群算法在求解移动节点覆盖优化问题时容易陷入早熟收敛的不足，研究了基于扰动因子的粒子群覆盖优化，该方法将扰动因子融入到粒子群算法的速度更新公式中，通过扰动粒子速度指导粒子进化；另外，将量子理论和粒子群算法相结合，研究了基于量子粒子群算法覆盖优化，该方法利用量子空间中粒子满足集聚态性质完全不同的特点，在整个可行空间内进行搜索，避免了粒子群算法容易陷入局部最优的问题。结果表明，两种改进算法均能改善网络覆盖性能，并且量子粒子群方法可以减少平均移动距离，达到节能覆盖的目的。
关键词 无线传感器网络；覆盖优化；能量有效；遗传算法；粒子群算法
Abstract
Wireless sensor network is composed of a large number of energy limited micro-sensor nodes distributed in the monitoring regions, which have the sensing, computing and communicating capabilities through self-organized manner. Before the specific applications, the methods of deploying the sensor nodes should be determined according to the criteria of application-specific environments. As one of the fundamental problems in the wireless sensor network, the researches of coverage focus on the case that how to maximize the coverage regions and achieve the reliable area observation with quality of service.
Based on the problem of coverage, with the consideration of energy efficiency, this paper discusses and researches energy efficient coverage optimization of wireless sensor network. The main research works are as follows:
1. Energy-balanced coverage strategy
To solve the problems of coverage overlap、excessive energy consumption and communication conflicts caused by deploying nodes with high density, based on the selection of the optimal coverage set of nodes, an energy-balanced coverage strategy is researched. A network of probabilistic sensing model is built and an energy balance coefficient is set. Network coverage, working nodes and energy consumption coefficient are the optimization goals, then the genetic algorithm is used to get the optimal coverage solution. Simulation results show that the strategy can reduce and balance the energy consumption while ensuring the high network coverage, thus making the network work stably and prolonging the network lifetime efficiently.
2. Energy-efficient coverage optimization of dynamic nodes
When used to solve the coverage optimization problem of dynamic nodes, PSO easily falls into the local optimum. So the coverage optimization based on disturbance-factor PSO is researched. The strategy adds a disturbance factor to the updating formula of PSO, thus guiding the evolution; Then, with the combination of quantum theory and PSO, the coverage optimization based on QPSO is researched. The aggregation characteristic of every particle in the quantum space is unique, so the algorithm can search throughout the entire feasible region. Thus the QPSO, of which global search ability is much better than PSO, can avoid the disadvantages of being easily trapped into a local extreme. Simulation results show that the proposed algorithms are better than PSO in coverage optimization and the algorithm based on QPSO can eliminate the mean moving distance of the nodes, thus meeting the aim of energy-efficient coverage.
Key words wireless sensor networks; coverage optimization; energy efficient; genetic algorithm; particle swarm optimization algorithm
目 录
摘 要 I
Abstract III
第1章 绪论 1
1.1 研究背景 1
1.1.1 无线传感器网络简介 1
1.1.2 无线传感器网络的特点 3
1.1.3 无线传感器网络的关键技术 4
1.1.4 无线传感器网络的研究现状与应用 5
1.2 课题研究目的和意义 5
1.3 本文的主要工作 6
1.4 本文的组织结构 7
第2章 无线传感器网络覆盖问题 9
2.1 引言 9
2.2 无线传感器网络覆盖分类 9
2.3 典型的覆盖算法分析 12
2.3.1 基于静态节点调度的覆盖算法 12
2.3.2 基于移动节点的覆盖算法 14
2.4 覆盖性能指标 16
2.5 覆盖算法评价标准 18
2.6 本章小结 19
第3章 基于遗传算法的能耗均衡覆盖策略 21
3.1 问题概述 21
3.1.1 传感器节点覆盖模型 22
3.1.2 网络覆盖模型 24
3.2 遗传算法原理 24
3.2..
