WSN中波纹式蔓延拓扑结构生成及自维护算法的研究

发布时间：2018-05-13 09:37

本文选题：无线传感器网络 + 拓扑结构生成　；参考：《辽宁大学》2017年硕士论文

【摘要】：无线传感器网络(Wireless Sensor Network,WSN)是将大量传感器节点随机播撒在监测区域中,分布式自组织成连通的网络;而生成及维护负载均衡的拓扑结构对于延长WSN的生命周期有重要作用。因此,针对WSN的特点与限制,以及农业环境监控的实际需求,提出了波纹式蔓延拓扑结构生成算法及其自维护算法。本文主要内容如下:首先,本文对WSN及拓扑控制技术相关概念进行概述,并对国内外的研究现状和先进的拓扑控制算法进行深入研究与分析,挖掘其中存在的缺陷。其次,针对发现的问题及农产品生产环境的实际需求,本文提出了波纹式蔓延拓扑结构生成算法(Spreading Like Ripples Topology Generation Algorithm,SLR-TG)。该算法以Sink节点为中心,在其邻居节点中,考虑到节点的间距、节点的密度和节点的剩余能量,选择最优簇头加入主干网;然后,对所选簇头的邻居节点进行分簇;接着,选出的簇头重复Sink节点的操作,向周围一圈一圈蔓延扩散;最后,快速地生成负载均衡的拓扑网络。再次,针对主干网上的簇头节点因进行数据融合和频繁地通信导致节点能量消耗过快而产生的网络热点问题和因节点能量耗尽或环境等因素导致节点失效而产生的网络空洞问题,本文提出了拓扑结构自维护算法(Spreading Like Ripples Topology Automatic Maintenance Algorithm,SLR-TAM)。该算法会自动检测能量低于阈值及失效的簇头节点,自动寻找最优的替代节点作为新的簇头,修复断开的网络,使得网络重新连通,增加网络的寿命。最后,利用仿真软件NS-2对本文提出算法的性能进行验证,得出以下结论:本文提出的SLR-TG算法和SLR-TAM算法与Improved-LEACH算法、LEUC算法、RCS算法相比,簇头数目变化更加平稳,拓扑结构的负载和能耗更加均衡,提升了网络的生命周期。
[Abstract]:Wireless Sensor Network (WSNs) is a distributed self-organizing network that distributes a large number of sensor nodes randomly in the monitoring area, and the generation and maintenance of a load-balanced topology plays an important role in prolonging the lifetime of WSN. Therefore, according to the characteristics and limitations of WSN, and the actual needs of agricultural environment monitoring, a corrugated spread topology generation algorithm and its self-maintenance algorithm are proposed. The main contents of this paper are as follows: firstly, this paper summarizes the related concepts of WSN and topology control technology, and deeply studies and analyzes the current research situation and advanced topology control algorithms at home and abroad. Secondly, aiming at the problems found and the actual demand of the agricultural production environment, this paper proposes a corrugated Like Ripples Topology Generation algorithm to generate the corrugated Like Ripples Topology Generation algorithm SLR-TGG. The algorithm takes the Sink node as the center, considers the distance of the nodes, the density of the nodes and the residual energy of the nodes, and selects the optimal cluster head to join the backbone network. Then, the neighbor nodes of the selected cluster heads are clustered. The selected cluster head repeats the operation of the Sink node and spreads around it. Finally, the load balancing topology network is generated quickly. Again, Aiming at the network hot spot problem caused by data fusion and frequent communication of cluster head node on backbone network and the network void problem caused by node energy depletion or environment, etc., the cluster head node on the backbone network has the problem of network hot spot caused by data fusion and frequent communication, and the network void problem caused by the node energy depletion or environmental factors, etc. In this paper, a topology self-maintenance algorithm is presented. The algorithm will automatically detect cluster head nodes whose energy is lower than threshold and failure, and automatically find the optimal replacement node as the new cluster head, repair the broken network, make the network reconnect and increase the network lifetime. Finally, the performance of the proposed algorithm is verified by the simulation software NS-2, and the following conclusions are drawn: compared with the Improved-LEACH algorithm, the SLR-TG algorithm and the SLR-TAM algorithm are more stable than the Improved-LEACH algorithm. The load and energy consumption of topology are more balanced, and the life cycle of the network is improved.
【学位授予单位】：辽宁大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP212.9;TN929.5

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