室内无线传感器网络环境自适应定位和路由算法研究

发布时间：2018-05-07 16:11

本文选题：室内无线传感器网络 + 环境自适应　；参考：《大连理工大学》2014年博士论文

【摘要】：近年来,互联网正不断朝着物联网(IoT, Internet of Things)方向发展,而IoT中连接的很多物体都要求具有感知环境和测试数据的能力,因此无线传感器网络(WSN,Wireless Sensor Networks)技术成为IoT发展的重要技术支撑,针对WSN的室内应用需求也随之不断增多。然而,现有的WSN关键技术大多适用于室外或者理想环境,在复杂的室内环境下的应用效果却并不理想。因此,本文对室内WSN中的定位和路由算法进行了深入研究,其主要内容和研究成果如下： (1)通过对家居环境、办公环境和芯片生产环境测试数据的分析,总结了WSN在室内环境下的信号传输特征,为WSN在室内环境下的关键技术研究提供可靠依据。 (2)针对典型的室内环境进行了无线传感器节点的信道传输特性测试,并对测试数据进行了拟合。拟合结果表明,与经典的单折线和双折线模型相比,提出的三阶多项式对数距离路径损耗模型能够更好地表征WSN在室内环境下的信道衰落情况。 (3)WSN用于复杂的室内环境时,无线信道随环境变化的衰落使得自适应地评估目标节点的位置变得非常困难。因此,本文分别提出了基于单折线模型和基于三阶多项式模型的WSN室内环境自适应定位算法。在两种算法中,计算机首先利用固定节点传来的数据建立模型的参数集合,并根据环境的变化定时更新该集合；接下来,利用提出的参数选择方法搜索并确定模型参数；最后,分别采用迭代的方法和最大似然估计的方法对目标节点进行定位。实验测试结果验证了两种定位算法良好的定位精度。 (4)针对静态的理想室内环境,提出了一种能量均衡的稳定分簇路由算法EBSC(Energy-Balanced Steady Clustering),该算法每轮产生的簇头数量稳定,综合了分布式和集中式分簇算法的优点；针对动态的复杂室内环境,提出了一种能量均衡的自适应分簇路由算法EBACR (Energy-Balanced Adaptive Clustering Routing),该算法根据传输路径损耗和剩余能量信息选择各类节点,并采用不同主观系数的多属性决策方法,自适应地建立路由。实验结果表明,以上两种算法不仅高效地利用了网络节点有限的能量,而且均衡了节点的能量消耗。 (5)针对芯片生产企业对环境的严格要求,设计了基于WSN的芯片生产超净间环境监测系统,并在系统中利用了本文提出的EBACR算法建立路由。通过在芯片生产超净间的测试,验证了该系统不仅能够实时监测环境变化,而且能够保证传感器节点能量消耗的有效性和均衡性。
[Abstract]:In recent years , the Internet is growing in the direction of Internet of Things , while many objects connected in the Internet are required to have the capability of sensing environment and test data . Therefore , the wireless sensor networks ( WSN ) technology has become an important technical support for the development of the Internet . Therefore , the wireless sensor networks ( WSN , Wireless Sensor Networks ) technology has become an important technical support for the development of the Internet . However , the key technologies of the existing WSN are mostly suitable for outdoor or ideal environments , and the application effect in the complex indoor environment is not ideal . Therefore , the paper studies the positioning and routing algorithms in the indoor WSN , and the main contents and the research results are as follows :

( 1 ) Based on the analysis of home environment , office environment and chip production environment test data , this paper summarizes the signal transmission characteristics of WSN in indoor environment , and provides a reliable basis for the key technology research of WSN in indoor environment .

( 2 ) For the typical indoor environment , the channel transmission characteristics of wireless sensor nodes are tested and the test data is fitted . The fitting results show that the proposed third order polynomial log distance path loss model can better characterize the channel fading in the indoor environment compared with the classical single - fold line and the double - fold line model .

( 3 ) When WSN is used in a complex indoor environment , the fading of the wireless channel changes with the environment makes it very difficult to adaptively evaluate the location of the target node . In the two algorithms , the computer firstly uses the data from the fixed node to establish the parameter set of the model , and updates the set according to the change timing of the environment .
next , using the proposed parameter selection method to search and determine the model parameters ;
Finally , the method of iteration and the method of maximum likelihood estimation are used to locate the target nodes . The experimental results verify the good positioning accuracy of the two positioning algorithms .

( 4 ) Aiming at the ideal indoor environment , an energy - balanced cluster routing algorithm EBSC ( Energy - Balanced Clustering Algorithm ) is proposed . The number of cluster heads generated per wheel is stable , and the advantages of distributed and centralized clustering algorithm are integrated .
In this paper , an energy - balanced adaptive clustering routing algorithm EBACR ( Energy - Balanced Adaptive Routing Routing ) is proposed for dynamic complex indoor environment . The algorithm selects all kinds of nodes based on the transmission path loss and the residual energy information , and establishes the route adaptively . The experimental results show that the above two algorithms not only effectively utilize the limited energy of the network node , but also balance the energy consumption of the nodes .

( 5 ) According to the strict requirement of the chip production enterprise to the environment , the super clean room environment monitoring system based on WSN is designed , and the EBACR algorithm proposed in this paper is used to establish the route in the system . Through the test on the chip production supernet , the system can not only monitor the environment change in real time , but also can ensure the effectiveness and balance of energy consumption of the sensor node .

【学位授予单位】：大连理工大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TN929.5;TP212.9

【参考文献】