智能无线传感器网络中网络设计、路由和定位方法研究
发布时间：2021-11-07 09:09
随着科学技术的进步,智能无线传感器网络的应用前景广阔。无处不在的无线连接和多媒体应用的持续增长对无线传感器网络提出了更高的要求。特别地,在没有能源采集源的情况下,网络中节点的电池容量有限,无线传感器网络需要更高的能源效率。分簇网络设计和节能路由协议是无线传感器网络中提高能源效率的重要手段。分簇无线传感器网络是能量受限的网络,它与网络生命周期和吞吐量问题密不可分,通过簇头的最优选择来解决诸如“热点”之类的能量不平衡问题,在分簇网络设计中是一种合理的举措;频繁的重新分簇过程以及相应的路由变化会产生较大的消息广播开销,进而导致较高的能量消耗。为了解决上述问题,通过能量感知路由来最小化现有协议中的计算开销,有助于节省能耗,并最终使得网络整体性能最大化。本文研究了无线传感器网络中的分簇网络设计、能效分簇路由、吞吐率优化以及三维节点定位问题。本文的主要创新工作如下:（1）在无线传感器网络中,现有的网络性能优化技术需要进一步改进。为此,本文针对大规模无线传感器网络,提出一种混合分簇网络设计方法。该方法首先应用磁盘分区的思想,将大规模网络分成水波纹形状的分簇,并用功率调整技术来设计由基站初始化的同心层...
【文章来源】：大连理工大学辽宁省 211工程院校 985工程院校 教育部直属院校
【文章页数】：128 页
【学位级别】：博士
【文章目录】：
ABSTRACT
摘要
List of Abbreviations
1 Introduction
1.1 Research Background and Significance
1.2 State of the Art of the Related Research
1.2.1 Efficient Cluster/Network Design
1.2.2 Efficient CH Selection
1.2.3 Network Throughput Optimization
1.2.4 3-D Node Localization
1.3 Main Contents and Organization of the Dissertation
2 Background Knowledge
2.1 Introduction
2.2 Network Design
2.2.1 Features of WSN
2.2.2 Traditional Clustered WSN
2.2.3 IoT and Smart WSN
2.2.4 System Architecture
2.3 Network Lifetime
2.3.1 Reasons for Energy Waste
2.3.2 Classification of Energy Efficient Routing
2.4 Throughput Optimization in WSN
2.4.1 Energy Aware Routing and Performance Evaluation
2.4.2 Schedule Length
2.4.3 Network Throughput
2.4.4 Average End to End Delay
2.4.5 Average Maximum Queue Length
2.5 Node Localization in Wireless Sensor Network
2.5.1 Research Issues
2.5.2 Deployment Strategy
2.5.3 Localization
2.5.4 Node Localization Techniques
2.5.5 RSSI Measurement Algorithm
2.5.6 Received Signal Strength Indicator
2.6 Research Challenges
2.7 Summary
3 Water Rippling Shaped Clustering Strategy for Efficient Performance of Wireless SensorNetworks
3.1 Introduction
3.2 System Model
3.2.1 Energy Consumption in Data Communications for One Round
3.2.2 Network Model
3.3 Water Rippling Shaped Clustering Strategy
3.3.1 Construction of Layers
3.3.2 Cluster Size and Width
3.3.3 Cluster Design
3.3.4 Pivotal Area of Cluster Re-Clustering
3.3.5 Selection of Cluster Head
3.4 Simulation and Results Discussion
3.5 Summary
4 OPEN: Optimized Path Planning Algorithm with Energy Efficiency and Extending Network-Lifetime in WSN
4.1 Introduction
4.2 Network Design
4.2.1 Radio Model
4.3 Optimized Path Planning Algorithm
4.3.1 Cluster Organization Phase
4.3.2 Neighbor Information Collection Phase
4.3.3 Cluster Head Election Phase
4.3.4 Node Association Phase
4.3.5 Cluster Communication Phase
4.3.6 Transmission Phase
4.4 Simulations and Results Discussion
4.5 Summary
5 Inter-operable and Energy Aware Routing for Throughput Optimization in Clustered IoT-Wireless Sensor Networks
5.1 Introduction
5.2 Energy Consumption Model
5.3 Features of Energy and Inter-operable Aware Routing Scheme
5.4 Energy and Inter-operable Aware Routing Scheme
5.4.1 Path Set-up Phase (Route Discovery)
5.4.2 Cluster Formation
5.4.3 Cluster Head Rotation
5.4.4 Network Operation Phase
5.4.5 Comparative Analysis of Proposed Scheme with three Variants of LEACH
5.5 Simulation Results and Discussion
5.6 Summary
6 3-D Weighted Centroid Algorithm & RSSI Ranging Model Strategy for Node Localiza-tion in WSN Based on Smart Devices
6.1 Introduction
6.2 Localization Architecture
6.3 3-D Weighted Centroid Algorithm and RSSI Ranging Model Strategy
6.3.1 Received Signal Strength Indicator (RSSI)
6.3.2 RSSI Ranging Principles
6.3.3 Maximum Likelihood Estimation Method
6.3.4 3-D Positioning Algorithm with Weighted Centroid Localization
6.3.5 RSSI Measurement Algorithm
6.4 Simulation and Results Discussion
6.5 Summary
7 Conclusion and Future Work
7.1 Conclusion
7.2 Abstract of Innovation Points
7.3 Future Work
References
Published Academic Articles during PhD period
Acknowledgements
Author Introduction
【参考文献】：
期刊论文
[1]D-S Evidence Theory Based Trust Ant Colony Routing in WSN[J]. Ziwen Sun,Zhiwei Zhang,Cheng Xiao,Gang Qu. 中国通信. 2018(03)
[2]Fog Computing Architecture-Based Data Acquisition for WSN Applications[J]. Guangwei Zhang,Ruifan Li. 中国通信. 2017(11)
[3]改进的无线传感器网络节点定位算法[J]. 张宏君,毛永毅. 计算机应用. 2012(08)
[4]基于位置的服务:架构与进展[J]. 周傲英,杨彬,金澈清,马强. 计算机学报. 2011(07)
[5]BPEC:无线传感器网络中一种能量感知的分布式分簇算法[J]. 周新莲,吴敏,徐建波. 计算机研究与发展. 2009(05)
[6]基于LEACH协议的簇头多跳（LEACH-M）算法[J]. 李岩,张曦煌,李彦中. 计算机工程与设计. 2007(17)
[7]EADEEG:能量感知的无线传感器网络数据收集协议[J]. 刘明,曹建农,陈贵海,陈力军,王晓敏,龚海刚. 软件学报. 2007(05)
本文编号：3481578
【文章来源】：大连理工大学辽宁省 211工程院校 985工程院校 教育部直属院校
【文章页数】：128 页
【学位级别】：博士
【文章目录】：
ABSTRACT
摘要
List of Abbreviations
1 Introduction
1.1 Research Background and Significance
1.2 State of the Art of the Related Research
1.2.1 Efficient Cluster/Network Design
1.2.2 Efficient CH Selection
1.2.3 Network Throughput Optimization
1.2.4 3-D Node Localization
1.3 Main Contents and Organization of the Dissertation
2 Background Knowledge
2.1 Introduction
2.2 Network Design
2.2.1 Features of WSN
2.2.2 Traditional Clustered WSN
2.2.3 IoT and Smart WSN
2.2.4 System Architecture
2.3 Network Lifetime
2.3.1 Reasons for Energy Waste
2.3.2 Classification of Energy Efficient Routing
2.4 Throughput Optimization in WSN
2.4.1 Energy Aware Routing and Performance Evaluation
2.4.2 Schedule Length
2.4.3 Network Throughput
2.4.4 Average End to End Delay
2.4.5 Average Maximum Queue Length
2.5 Node Localization in Wireless Sensor Network
2.5.1 Research Issues
2.5.2 Deployment Strategy
2.5.3 Localization
2.5.4 Node Localization Techniques
2.5.5 RSSI Measurement Algorithm
2.5.6 Received Signal Strength Indicator
2.6 Research Challenges
2.7 Summary
3 Water Rippling Shaped Clustering Strategy for Efficient Performance of Wireless SensorNetworks
3.1 Introduction
3.2 System Model
3.2.1 Energy Consumption in Data Communications for One Round
3.2.2 Network Model
3.3 Water Rippling Shaped Clustering Strategy
3.3.1 Construction of Layers
3.3.2 Cluster Size and Width
3.3.3 Cluster Design
3.3.4 Pivotal Area of Cluster Re-Clustering
3.3.5 Selection of Cluster Head
3.4 Simulation and Results Discussion
3.5 Summary
4 OPEN: Optimized Path Planning Algorithm with Energy Efficiency and Extending Network-Lifetime in WSN
4.1 Introduction
4.2 Network Design
4.2.1 Radio Model
4.3 Optimized Path Planning Algorithm
4.3.1 Cluster Organization Phase
4.3.2 Neighbor Information Collection Phase
4.3.3 Cluster Head Election Phase
4.3.4 Node Association Phase
4.3.5 Cluster Communication Phase
4.3.6 Transmission Phase
4.4 Simulations and Results Discussion
4.5 Summary
5 Inter-operable and Energy Aware Routing for Throughput Optimization in Clustered IoT-Wireless Sensor Networks
5.1 Introduction
5.2 Energy Consumption Model
5.3 Features of Energy and Inter-operable Aware Routing Scheme
5.4 Energy and Inter-operable Aware Routing Scheme
5.4.1 Path Set-up Phase (Route Discovery)
5.4.2 Cluster Formation
5.4.3 Cluster Head Rotation
5.4.4 Network Operation Phase
5.4.5 Comparative Analysis of Proposed Scheme with three Variants of LEACH
5.5 Simulation Results and Discussion
5.6 Summary
6 3-D Weighted Centroid Algorithm & RSSI Ranging Model Strategy for Node Localiza-tion in WSN Based on Smart Devices
6.1 Introduction
6.2 Localization Architecture
6.3 3-D Weighted Centroid Algorithm and RSSI Ranging Model Strategy
6.3.1 Received Signal Strength Indicator (RSSI)
6.3.2 RSSI Ranging Principles
6.3.3 Maximum Likelihood Estimation Method
6.3.4 3-D Positioning Algorithm with Weighted Centroid Localization
6.3.5 RSSI Measurement Algorithm
6.4 Simulation and Results Discussion
6.5 Summary
7 Conclusion and Future Work
7.1 Conclusion
7.2 Abstract of Innovation Points
7.3 Future Work
References
Published Academic Articles during PhD period
Acknowledgements
Author Introduction
【参考文献】：
期刊论文
[1]D-S Evidence Theory Based Trust Ant Colony Routing in WSN[J]. Ziwen Sun,Zhiwei Zhang,Cheng Xiao,Gang Qu. 中国通信. 2018(03)
[2]Fog Computing Architecture-Based Data Acquisition for WSN Applications[J]. Guangwei Zhang,Ruifan Li. 中国通信. 2017(11)
[3]改进的无线传感器网络节点定位算法[J]. 张宏君,毛永毅. 计算机应用. 2012(08)
[4]基于位置的服务:架构与进展[J]. 周傲英,杨彬,金澈清,马强. 计算机学报. 2011(07)
[5]BPEC:无线传感器网络中一种能量感知的分布式分簇算法[J]. 周新莲,吴敏,徐建波. 计算机研究与发展. 2009(05)
[6]基于LEACH协议的簇头多跳（LEACH-M）算法[J]. 李岩,张曦煌,李彦中. 计算机工程与设计. 2007(17)
[7]EADEEG:能量感知的无线传感器网络数据收集协议[J]. 刘明,曹建农,陈贵海,陈力军,王晓敏,龚海刚. 软件学报. 2007(05)
本文编号：3481578
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