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无线传感器网络中的数据处理与数据传输技术研究
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摘要
无线传感器网络(Wireless Sensor Networks)是一种低成本、低功耗、分布式的多跳自组织网络,是近年来在国内外新兴的前沿研究领域,其研究内容涉及无线通信技术、嵌入式技术、传感器技术、分布式处理技术以及微机电技术(MEMS)。无线传感器网络在军事应用、环境科学、医疗保健、工业应用、商务应用等领域有着广阔的应用前景和实用价值。美国商业周刊在预测未来技术发展的报告中,将它列为21世纪最具影响力的21项发明之一,MIT则将它列为改变世界10大关键技术之一,而被美国时代周刊评为2008年全球50大发明之一的“物联网(Internet of things)”,更被认为是无线传感器网络的未来发展方向。
     无线传感器网络是一种全新的信息获取平台,其分布在监测环境中的节点通过无线多跳传输的方式将监测信息发送给信息收集节点(Sink)。无线传感器网络与传统传感器监测网络有较大不同,其具有以数据收集为中心、节点能量有限、应用相关性强等特点,因此在拓扑控制、网络协议、数据收集与处理、应用系统等方面有较多关键技术。本篇论文以无线传感器网络中的数据处理与数据收集技术为研究中心,研究以环境监测为应用背景,以低能耗为目标,围绕无线传感器网络在数据处理与数据传输中的关键技术展开研究。
     数据处理是无线传感器网络中的一个基本和关键的问题,它通常会对节点上报的数据进行处理,形成融合、压缩后的数据以减少网络中的通信量,节省网络能量。本篇论文首先以环境监测为应用背景,针对等值线数据处理技术在无线传感器网络中的应用展开研究工作,取得的主要研究成果及创新点如下:
     (1)论述了无线传感器网络在环境监测中的数据收集与处理时面临的问题,总结了国内外研究现状以及不足。
     (2)针对环境监测应用中的能量约束问题,提出一种应用于无线传感器网络中,基于最小二乘准则的Bezier曲线拟合等值线技术LS-T。该算法从等值线的曲线特性出发,利用Bezier曲线拟合等值线,从数据源处对数据进行处理,减少节点汇报的数据,从而有效的降低了网络的能耗。
     (3)在分析了无线传感器网络节点的能耗,发现无线收发模块的能耗为节点主要能耗,且LS-T算法在实施过程中无线收发数据逐级增加的缺点后,在LS-T算法的基础之上,本文提出一种能量高效的等值线监测方法SENS-T。SENS-T算法采取计算一次传输一次的思想,控制了分段等值线上报数据的大小,从而进一步降低了网络通信量。与国内外现有方法进行对比,该方法在达到相同监测效果的情况下,可节省约45%的网络能量。
     数据传输技术同样是无线传感器网络的关键技术之一,本文同样研究了无线传感器网络的路由与数据回传协议,具体工作及创新点如下:
     (1)在结合地理路由与能量梯度路由特点的基础上,本文提出一种基于矢量合成的路由策略ED,该策略为需传输数据的节点建立指向Sink的方向单位矢量,依照节点周边节点的剩余能量建立能量单位矢量。在对两个矢量进行加权后,通过计算合矢量确定路由的下一跳节点。该策略考虑数据回传方向性的同时,兼顾了网络的能耗,实验证明其较能量梯度路由能够降低网络能耗,使无线传感器网络的能耗均衡消耗。
     (2)针对距离Sink较近的节点能耗消耗过快的问题,本文设计了一种轮替式传输方法Triple-T,该方法在利用时钟同步技术的同时,采用节点间歇性休眠的方式使得距离Sink较近的节点能量消耗均衡,节省了网络能耗。
Wireless Sensor Networks (WSNs) is a low-cost, low power, distributed multi-hopself-organized networks. It’s a cutting-edge of research filed started recent years homeand abroad. The study includes wireless communication technology, embeddedtechnology, sensor technology, distributed processing technology and MEMStechnology. Wireless Sensor Networks has a great application prospect and practicalvalue in military, environmental science, health care, industry, business and so on. Inthe Business Week’s report of the future technology predictions, WSN is listed as themost influential21inventions in the21st century. MIT lists WSN as one of10keytechnologies that change the world. For “Internet of things” which is one of50inventions evaluated by Time magazine, is treated as the future research direction ofWireless Sensor Networks.
     Wireless sensor network is a new information acquisition platform. By usingwireless multi-hop transmission method, WSN’s nodes that scattered on observationenvironment transmit monitoring information back to Sink. Wireless sensor networksand traditional networks have lots of differences. Wireless sensor network havecharacters such as data collection-centric, limited energy of nodes, applicationcorrelation, so there’s many key research challenges such as topology control,network protocols, data collection and processing, application system. In this thesis,our main research interests, based on environmental monitoring application, focus onkey research challenges such as data processing and data collection. Our goal is toreach network energy-efficiency.
     Data processing is a fundamental and key challenge in wireless sensor networks, itusually processes the data reported by nodes, from fused, compressed data to reducenetwork transmission and save network energy. This paper’s research based onenvironmental monitoring, aim to use contour mapping processing technology intowireless sensor network. The main research contents and contributions of this thesisare as follows:
     1. Discusses problems and challenges of data processing and data collection inwireless sensor networks.
     2. Aiming to the energy-constraint problem in environmental monitoringapplication, we propose a contour mapping scheme based on least-square Bezierfitting which used in wireless sensor networks. This scheme focuses on the curvefeature of contour lines. By using Bezier curves fits contour lines, this schemeprocesses data form data source, reduces the amount of nodes’ data, and thenreduces network energy consumption efficiently.
     3. In the analysis of wireless transceiver modules,and realized that this is themajor energy consumption of wireless sensor network, while noticing theshortcomings of LS that LS brings data accumulation will forming Bezier curves.This paper introduces a novel energy-efficient contour mapping scheme based onLS-T algorithm, and named this algorithm SENS-T. SENS-T takes the thought thatBezier curve is calculated on each node before transmission, so it restraints theamount data of Bezier curves segment, and further reduces network traffic. Bycomparing existing methods, SENS-T achieves the same monitoring accuracy whilereducing45%of the network energy.
     Data transmission technology is also one of the key research challenges ofwireless sensor networks, our work also studies routing and data collectionprotocol of wireless sensor networks, and the main research contents andcontributions of this thesis are as follows:
     1. In the combination of the features of geographic routing and energy gradientrouting, this paper presents a routing strategy based on vector synthesis named ED.this strategy constructs a directional unit vector by using node in the direction ofpointing Sink. According to the residual energy of neighboring nodes around thenode, this strategy establishes an energy unit vector. After these two unit vectors areweighted, the next hop routing node is calculated. This strategy considers thedirection of data streams while taking into account the energy consumption of thenetwork. Comparing whit existing methods, our test proves that it reduces thenetwork energy consumption while balancing energy consumption of sensor networks.
     2. Aiming to the problem of the nodes that close to Sink are always shoulderexcessive energy consumption, the paper design a rotation-type transmissionmethod. While nodes using time synchronization, nodes adopts intermittent sleepway to fulfill the mission of energy consumption reduction of nodes that next toSink and balances the network energy consumption.
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