无线传感器网络路由算法与能耗模型研究及仿真

发布时间：2018-09-04 15:15

【摘要】：无线传感器网络是以传感器技术、通信技术、计算机技术为基础的现代信息技术,在军事、农业、环境监测、医疗卫生、工业、智能交通、建筑物监测、空间探索等领域有着广阔的应用前景和巨大的应用价值,被认为是未来改变世界的十大技术之一。同时,无线传感器网络也是能量严重受限的网络。由于传感器节点的能量有限,无线传感器网络的路由、数据融合、定位和时间同步等研究都要考虑到节点的剩余能量。节点的剩余能量可以通过能耗模型计算得出,能耗模型是无线传感器网络的研究重点之一。在能量有限的无线传感器网络中,对无线传感器节点能量消耗的监测非常重要,无线传感器节点的能耗模型是能耗监测的理论基础。以农业灌溉系统为例,对农业应用领域,提出了面向农业的无线传感器网络节点设计、部署设计、路由设计和控制端设计。并针对路由节点异常问题,提出了一种面向农业的无线传感器网络路由恢复算法。在能耗模型研究方面,针对无线传感器网络节点硬件的模块划分,尤其针对处理器、模数转换器和存储器等模块,改进了现有的无线传感器节点能耗模型。根据能耗模型设计了TinyOS2.x的能耗计算组件,能耗计算组件基于参数化方案设计,能够支持多种类型传感器节点的能量监测。现有的TinyOS2.x仿真工具TOSSIM只能在字符界面中进行无线传感器网络仿真,必须根据字符界面的消息获知节点的运行情况。并且TOSSIM还不具备对节点能量监测的功能。为了改进现有TOSSIM的不足,根据改进的能耗模型,提出了一种无线传感器节点的剩余能量计算算法。根据剩余能量计算算法,设计了可计算节点剩余能量的TinyOS2.x剩余能量计算组件和传感器节点应用程序,并通过Qt软件开发技术设计了图形化仿真软件。图形化仿真软件通过读取传感器节点应用程序消息获得节点的信息,并在无线传感器网络仿真过程中显示各个传感器节点的通信和剩余能量情况。对面向农业的无线传感器网络路由恢复算法和动态源路由算法分别进行仿真。仿真结果表明,在路由恢复过程中,面向农业的无线传感器网络路由恢复算法通信数据包数量比动态源路由算法更少,可以降低节点的通信能耗。为了验证能耗模型,在TinyOS2.0的上实现无线传感器节点能耗仿真功能。同时,在仿真平台和真实硬件平台上进行能耗数据采集,通过仿真与实测数据对比,说明了能耗模型的有效性。对图形化仿真软件进行测试验证,测试表明图形化仿真软件可以直观、准确的对无线传感器网络进行仿真。
[Abstract]:Wireless sensor network is a modern information technology based on sensor technology, communication technology, computer technology, in military, agriculture, environmental monitoring, medical and health, industry, intelligent transportation, building monitoring, Space exploration and other fields have broad application prospects and great application value, and are considered to be one of the ten technologies that will change the world in the future. At the same time, wireless sensor networks are also severely limited energy networks. Due to the limited energy of sensor nodes, the research on routing, data fusion, location and time synchronization of wireless sensor networks should take into account the residual energy of nodes. The residual energy of nodes can be calculated by energy consumption model, which is one of the key research points in wireless sensor networks. In wireless sensor networks with limited energy, it is very important to monitor the energy consumption of wireless sensor nodes. The energy consumption model of wireless sensor nodes is the theoretical basis of energy consumption monitoring. Taking the agricultural irrigation system as an example, the design of the node, deployment, routing and control terminal of the wireless sensor network for agriculture is proposed. Aiming at the problem of routing node anomaly, an agri-oriented routing recovery algorithm for wireless sensor networks is proposed. In the research of energy consumption model, the existing energy consumption model of wireless sensor nodes is improved, especially for the modules of processor, A / D converter and memory. According to the energy consumption model, the energy consumption calculation module of TinyOS2.x is designed, which is based on parameterized scheme design and can support the energy monitoring of various sensor nodes. The existing TinyOS2.x simulation tool TOSSIM can only simulate the wireless sensor network in the character interface and must know the running condition of the node according to the message of the character interface. Moreover, TOSSIM does not have the function of monitoring node energy. In order to improve the shortcomings of the existing TOSSIM, an algorithm for calculating the residual energy of wireless sensor nodes is proposed according to the improved energy consumption model. According to the residual energy calculation algorithm, the TinyOS2.x residual energy computing module and sensor node application program are designed, and the graphical simulation software is designed by Qt software development technology. The graphical simulation software obtains the node information by reading the message of sensor node application program, and displays the communication and residual energy of each sensor node in the simulation process of wireless sensor network. The routing recovery algorithms and dynamic source routing algorithms for agricultural wireless sensor networks are simulated. The simulation results show that the number of communication packets in agricultural wireless sensor network routing recovery algorithm is less than that of dynamic source routing algorithm, which can reduce the communication energy consumption of nodes. In order to verify the energy consumption model, the energy consumption simulation function of wireless sensor nodes is implemented on TinyOS2.0. At the same time, the energy consumption data is collected on the simulation platform and the real hardware platform. The validity of the energy consumption model is illustrated by comparing the simulation data with the measured data. The graphical simulation software is tested and verified. The test results show that the graphical simulation software can be used to simulate wireless sensor networks intuitively and accurately.
【学位授予单位】：兰州交通大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TP212.9;TN929.5

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