基于改进克里金算法的WSNs环境监测方法研究

发布时间：2018-05-09 14:29

本文选题：环境监测 + 无线传感器网络　；参考：《南京邮电大学》2017年硕士论文

【摘要】：随着信息技术的发展和进步,物联网(Internet of Things,IoT)逐步融入社会生活的各个方面,在工业生产、环境监测、医疗健康等众多领域都得到了广泛的应用。无线传感器网络(Wireless Sensor Networks,WSNs)是物联网的基础设施与关键技术之一,具有自组织、规模庞大、分布密集等特征。受节点成本的限制,网络的能量资源、计算资源、存储资源等均很有限。在这种情况下,如何提高网络性能是WSNs应用研究的重点。本文主要对基于WSNs的环境监测方法进行了研究。节点调度算法是一种能有效延长WSNs生命周期的方法,但是节点的休眠会引起监测数据的缺失,从而导致监测精度的降低。因此本文利用克里金算法来估计缺失的数据。本文首先针对普通克里金算法变异函数模型拟合精度不高的问题,引入基于高斯变异的NM单纯形法,提出了一种改进克里金算法(Improved Kriging,IK)。仿真结果表明,改进算法的估计精度要优于普通克里金算法。然后,将改进的克里金算法应用到WSNs中,并将其与能量均衡休眠调度算法相结合,提出了一种基于改进克里金的WSNs插值估计算法。仿真实验结果表明,本文提出的监测方法在延长网络生命周期的同时,也能够保证较好的监测精度。最后,本文基于克里金插值估计算法,设计并实现了一个WSNs环境监测仿真系统,并进行了演示。
[Abstract]:With the development and progress of information technology, Internet of things (Internet of things) has been gradually integrated into all aspects of social life. It has been widely used in many fields, such as industrial production, environmental monitoring, medical health and so on. Wireless Sensor Networks (WSNs) is one of the infrastructure and key technologies of the Internet of things. It has the characteristics of self-organization, large scale and dense distribution. Limited by node cost, network energy resources, computing resources, storage resources and so on are very limited. In this case, how to improve network performance is the focus of WSNs application research. In this paper, the method of environmental monitoring based on WSNs is studied. Node scheduling algorithm is an effective way to prolong the WSNs life cycle, but the node dormancy will lead to the lack of monitoring data, which leads to the decrease of monitoring accuracy. Therefore, the Kriging algorithm is used to estimate the missing data. Aiming at the problem that the fitting accuracy of the ordinary Kriging algorithm variogram model is not high, this paper introduces the NM simplex method based on Gao Si mutation, and proposes an improved Kriging algorithm to improve the Kriging algorithm. The simulation results show that the estimation accuracy of the improved algorithm is better than that of the ordinary Kriging algorithm. Then, the improved Kriging algorithm is applied to WSNs, and combined with the energy equilibrium sleep scheduling algorithm, a WSNs interpolation estimation algorithm based on improved Kriging is proposed. The simulation results show that the proposed method can not only prolong the network life cycle, but also ensure better monitoring accuracy. Finally, based on the Kriging interpolation estimation algorithm, a WSNs environment monitoring simulation system is designed and implemented.
【学位授予单位】：南京邮电大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP212.9;TN929.5

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