基于拓扑控制的物联网优化技术研究

发布时间：2018-06-13 23:49

本文选题：物联网 + 拓扑控制　；参考：《安徽理工大学》2017年硕士论文

【摘要】：随着科技的进步,经济的发展,物联网已经成为当今研究的热点,由于其功能强大以及很好的智能性,已经成为生活中不可或缺的一部分。因为物联网技术可以自动的获取周围的信息,这就使得网络节点在其扮演着中重要角色。网络节点一般都是大规模的组成一个拓扑结构,要想网络的生存时间长,这就要求网络拓扑结构应该设计的更加合理,也就是设计出能耗低的拓扑结构。所以一个性能更佳以及能量损耗更低的网络拓扑结构是当前重要的研究目标。本文主要对物联网中网络拓扑结构进行了分析和研究,对已有的算法进行改进,提出了基于遗传算法对LEACH拓扑算法的优化(LEACH-GA)。LEACH-GA算法在簇头选取的阶段,通过对阀值的修改,使得簇头的选择考虑的因素包括簇头的剩余能量、节点的邻居节点数以及节点是否当选过簇头等,这样选择出来的簇头会更加合理;另外在簇的建立阶段,利用遗传算法的适应度函数的计算值来确定更加合理的分簇结构。通过MATLAB仿真表明,改进后的算法在节点的生命周期以及数据发送量都有所提高,说明改进后的算法网络结构更加合理。本文结合网络节点以及提出的算法,设计出能够实现LEACH-GA算法的硬件电路,利用FPGA芯片来实现算法。实验结果表明LEACH-GA算法确实能够提高物联网中网络拓扑结构的能量利用率,从而延长物联网的网络生存时间。
[Abstract]:With the progress of science and technology and the development of economy, the Internet of things has become a hot spot of research today, because of its powerful function and good intelligence, it has become an indispensable part of life. Because the Internet of things technology can automatically obtain the surrounding information, this makes network nodes play an important role in it. Network nodes generally constitute a topology structure on a large scale. In order to live a long time, network topology should be designed more reasonably, that is, to design a topology with low energy consumption. Therefore, a network topology with better performance and lower energy loss is an important research goal. In this paper, the network topology in the Internet of things is analyzed and studied, the existing algorithms are improved, and the optimization of Leach topology algorithm based on genetic algorithm is proposed. In the stage of cluster head selection, the threshold is modified. The factors that make the cluster head selection consider include the residual energy of the cluster head, the number of neighbor nodes of the node and whether the node has been elected as the cluster head, so that the selected cluster head will be more reasonable; in addition, in the stage of cluster establishment, A more reasonable clustering structure is determined by using the computational value of fitness function of genetic algorithm. The MATLAB simulation shows that the improved algorithm can improve the node life cycle and data delivery, which indicates that the improved algorithm network structure is more reasonable. Combining the network node and the proposed algorithm, this paper designs the hardware circuit which can realize the LEACH-GA algorithm, and uses FPGA chip to realize the algorithm. The experimental results show that the LEACH-GA algorithm can improve the energy utilization rate of the network topology in the Internet of things, thus prolonging the network lifetime of the Internet of things.
【学位授予单位】：安徽理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP391.44;TN929.5

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