无线传感器网络节点动态采样策略研究

发布时间：2018-06-23 23:43

本文选题：无线传感器网络节点 + 数据采集　；参考：《安徽理工大学》2017年硕士论文

【摘要】：近年来,无线传感器网络技术受到了国际社会的广泛关注,随着传感器技术的日益成熟,其应用领域也越来越广。实际应用中,无线传感器网络节点通常被部署在比较复杂的环境中,其一般利用电池供电。能量有效性是无线传感器网络的关键性指标,如何提高传感器节点的能量有效性成为了无线传感器网络中最值得研究的问题之一。无线传感器网络节点内部主要有三个耗能模块,分别是信息处理模块、传感器模块和无线通信模块。无线传感器节点的无线通信模块的能耗相对其他两个模块来说是比较多的,对于整个无线传感网络来说,节点与节点之间用于无线通信所消耗的能量占据了整个无线传感网络能耗的绝大部分。由于时间相关性和空间相关性的存在,无线传感器节点在数据采集的过程中会产生很多冗余信息,减少无线传感器网络中冗余信息的产生能够大大减少能耗,从而提高能量的利用效率,这对延长无线传感网络的使用寿命是有利的。本文提出了一种无线传感器网络节点动态采样策略DSI,将当前采样数据与历史采样数据作对比之后引入负反馈调节的方法来动态确定传感器节点的采样间隔,以较低的采样频率、数据上传频度来满足信号测量的要求,从而降低能耗提高传感器节点能量有效性。本文用动态采样策略DSI与传统周期采样策略、SOD(Send-On-Delta)采样策略做了比较,并做了仿真验证,验证了动态采样策略DSI的优越性,动态采样策略DSI显著节约了节点能耗。
[Abstract]:In recent years, wireless sensor network (WSN) technology has received extensive attention from the international community. With the increasing maturity of sensor technology, its application field is becoming more and more extensive. In practical applications, wireless sensor network nodes are usually deployed in more complex environments, which generally use battery power. Energy efficiency is the key index of wireless sensor networks. How to improve the energy efficiency of sensor nodes has become one of the most worthy problems in wireless sensor networks. There are three energy dissipation modules in wireless sensor network nodes, which are information processing module, sensor module and wireless communication module. The energy consumption of wireless communication module of wireless sensor node is more than the other two modules, for the whole wireless sensor network, The energy consumed in wireless communication between nodes accounts for most of the total energy consumption of wireless sensor networks. Due to the existence of temporal and spatial correlation, wireless sensor nodes will produce a lot of redundant information in the process of data acquisition, and reduce the generation of redundant information in wireless sensor networks can greatly reduce energy consumption. Therefore, the energy utilization efficiency is improved, which is beneficial to prolong the service life of wireless sensor network. In this paper, a dynamic sampling strategy DSI for wireless sensor network nodes is proposed. After comparing the current sampling data with the historical sampling data, a negative feedback adjustment method is introduced to dynamically determine the sampling interval of the sensor nodes, and the sampling frequency is lower. The frequency of data upload can meet the requirement of signal measurement and reduce the energy consumption to improve the energy efficiency of sensor nodes. In this paper, the dynamic sampling strategy (DSI) is compared with that of the traditional periodic sampling strategy (Send-On-Delta), and the simulation results show that the dynamic sampling strategy (DSI) is superior to the dynamic sampling strategy (DSI), and the dynamic sampling strategy (DSI) saves the node energy consumption significantly.
【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】：TP212.9;TN929.5

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