本文選題：無線傳感網(wǎng)絡(luò) + 蟲洞　； 參考：《成都理工大學(xué)》2017年碩士論文

【摘要】：無線傳感器網(wǎng)絡(luò)(WSN)為人類提供了一種可以從數(shù)據(jù)角度去感知客觀世界的方式,其研究前景廣闊。隨著近年來的迅速發(fā)展,已在軍事、工業(yè)、環(huán)境監(jiān)測(cè)、醫(yī)療健康和日常生活中扮演著越來越重要的角色。無線傳感器網(wǎng)絡(luò)作為物聯(lián)網(wǎng)中的一種核心技術(shù),它在物聯(lián)網(wǎng)中與其他技術(shù)協(xié)同工作,共同所產(chǎn)生的經(jīng)濟(jì)效率和社會(huì)效益遠(yuǎn)遠(yuǎn)大于單種技術(shù)產(chǎn)生效益的總和。無線傳感器網(wǎng)絡(luò)與有線網(wǎng)絡(luò)和傳統(tǒng)的無線網(wǎng)絡(luò)有著巨大的不同之處,它僅由許多傳感感器節(jié)點(diǎn),沒有復(fù)雜、高效的管理設(shè)備用于管理網(wǎng)絡(luò)拓?fù)浣Y(jié)構(gòu)與各種協(xié)議。節(jié)點(diǎn)間的數(shù)據(jù)通信依靠自身與其他節(jié)點(diǎn)的相互覆蓋而形成的無線鏈路。因?yàn)闆]有集中式的管理設(shè)備,節(jié)點(diǎn)網(wǎng)絡(luò)拓?fù)涞男纬�、管理和維護(hù)都只能依靠節(jié)點(diǎn)本身。而無線傳感器網(wǎng)絡(luò)的工作環(huán)境往往比較惡劣,其拓?fù)浣Y(jié)構(gòu)中很有可能會(huì)出現(xiàn)蟲洞,從而帶來惡劣的影響,所以蟲洞檢測(cè)是無線傳感器網(wǎng)絡(luò)的中的一個(gè)重要研究課題。檢測(cè)和定位無線傳感器網(wǎng)絡(luò)的外邊界與蟲洞產(chǎn)生的內(nèi)邊界對(duì)網(wǎng)絡(luò)的穩(wěn)定性、工作效率與生命周期有著很強(qiáng)的關(guān)聯(lián)性。本文基于復(fù)雜網(wǎng)絡(luò)中的滲流理論對(duì)無線傳感器網(wǎng)絡(luò)的蟲洞進(jìn)行研究。本研究在無法獲取節(jié)點(diǎn)位置信息的前提下,以檢測(cè)網(wǎng)絡(luò)中蟲洞的邊界與網(wǎng)絡(luò)的外邊界為目標(biāo),研究相關(guān)的檢測(cè)算法與參數(shù)優(yōu)化。本文主要內(nèi)容如下:1)利用滲流理論中網(wǎng)絡(luò)中某一點(diǎn)的狀態(tài)突變會(huì)引起系統(tǒng)全局狀態(tài)發(fā)生改變的特點(diǎn),建立了回流模型�；亓髂Ｐ屯ㄟ^修改某個(gè)節(jié)點(diǎn)狀態(tài),然后分析處于不同位置節(jié)點(diǎn)的狀態(tài)改變情況;2)在回流模型的基礎(chǔ)上進(jìn)行無線傳感器網(wǎng)絡(luò)的邊界節(jié)點(diǎn)的識(shí)別形成邊界森林,最后通過最短路徑算法將邊界森林形成閉環(huán);3)通過仿真軟件進(jìn)行多組模擬實(shí)驗(yàn),對(duì)算法的準(zhǔn)確性進(jìn)行驗(yàn)證。并分析部分參數(shù)的優(yōu)化。本文提出的算法可以檢測(cè)出90%以上的邊界節(jié)點(diǎn),針對(duì)無線傳感感器中蟲洞檢測(cè)效果良好。
[Abstract]:Wireless sensor networks (WSNs) provide a way for human beings to perceive the objective world from the point of view of data. With the rapid development in recent years, it has played a more and more important role in military, industry, environmental monitoring, medical health and daily life. Wireless sensor network (WSN) is a core technology in the Internet of things. It works in collaboration with other technologies in the Internet of things, which results in far greater economic efficiency and social benefit than the sum of benefits produced by a single technology. Wireless sensor network has great difference from wired network and traditional wireless network. It is only composed of many sensor nodes without complex and efficient management equipment to manage network topology and various protocols. Wireless link formed by data communication between nodes by mutual coverage with other nodes. Because there is no centralized management equipment, node network topology formation, management and maintenance can only rely on the node itself. However, the working environment of wireless sensor networks is often bad, and wormholes are likely to appear in the topology of wireless sensor networks. Therefore, wormhole detection is an important research topic in wireless sensor networks. Detecting and locating the outer boundary of wireless sensor network and the inner boundary produced by wormhole have strong correlation with the network stability, work efficiency and life cycle. In this paper, wormholes of wireless sensor networks are studied based on percolation theory in complex networks. On the premise that the node location information can not be obtained, the detection of wormhole boundary and the outer boundary of the network are the targets of this study, and the related detection algorithms and parameter optimization are studied. The main contents of this paper are as follows: (1) based on the characteristic that the sudden change of the state at a certain point in the percolation theory can cause the change of the global state of the system, a reflux model is established. By modifying a node state and analyzing the state change of nodes in different locations, the reflux model is used to identify the boundary nodes of WSN to form a boundary forest based on the reflux model. Finally, the shortest path algorithm is used to form the boundary forest in closed loop. The simulation software is used to carry out multi-group simulation experiments to verify the accuracy of the algorithm. The optimization of some parameters is analyzed. The algorithm proposed in this paper can detect more than 90% of boundary nodes, and the detection effect of wormhole in wireless sensor is good.
【學(xué)位授予單位】：成都理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP212.9;TN929.5

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 張姿;黃廷磊;吳拱星;;一種改進(jìn)的邊界節(jié)點(diǎn)檢測(cè)算法[J];傳感技術(shù)學(xué)報(bào);2013年05期

2 高昊;王慶生;馮秀芳;史躍飛;;無線傳感器網(wǎng)絡(luò)中覆蓋盲區(qū)發(fā)現(xiàn)算法[J];傳感器與微系統(tǒng);2012年09期

3 高德民;錢煥延;徐江;王曉楠;;無線傳感器網(wǎng)絡(luò)隨機(jī)分布模型及覆蓋控制研究[J];傳感技術(shù)學(xué)報(bào);2011年03期

4 陶洋;曾曉玲;羅衛(wèi);;無線傳感器網(wǎng)絡(luò)中覆蓋控制算法研究及改進(jìn)[J];計(jì)算機(jī)應(yīng)用;2010年06期

5 蔣鵬;;一種改進(jìn)的DFD無線傳感器網(wǎng)絡(luò)節(jié)點(diǎn)故障診斷算法研究[J];傳感技術(shù)學(xué)報(bào);2008年08期

6 匡林愛;蔡自興;;一種無線傳感器網(wǎng)絡(luò)的節(jié)點(diǎn)自定位方法[J];計(jì)算機(jī)應(yīng)用;2008年02期

7 高建良;徐勇軍;李曉維;;基于加權(quán)中值的分布式傳感器網(wǎng)絡(luò)故障檢測(cè)(英文)[J];軟件學(xué)報(bào);2007年05期

8 張學(xué);陸桑璐;陳貴海;陳道蓄;謝立;;無線傳感器網(wǎng)絡(luò)的拓?fù)淇刂芠J];軟件學(xué)報(bào);2007年04期

9 任彥;張思東;張宏科;;無線傳感器網(wǎng)絡(luò)中覆蓋控制理論與算法[J];軟件學(xué)報(bào);2006年03期

10 蔣杰;方力;張鶴穎;竇文華;;無線傳感器網(wǎng)絡(luò)最小連通覆蓋集問題求解算法[J];軟件學(xué)報(bào);2006年02期

相關(guān)博士學(xué)位論文 前3條

1 尚小溥;基于圖相關(guān)理論的無線傳感器網(wǎng)絡(luò)若干拓?fù)鋯栴}研究[D];北京交通大學(xué);2015年

2 屈巍;無線傳感器網(wǎng)絡(luò)節(jié)點(diǎn)定位與覆蓋控制技術(shù)研究[D];東北大學(xué);2010年

3 楊挺;無線傳感器網(wǎng)絡(luò)QoS體系研究[D];天津大學(xué);2005年

相關(guān)碩士學(xué)位論文 前2條

1 孫繼忠;無線傳感器網(wǎng)絡(luò)柵欄覆蓋的研究[D];西南交通大學(xué);2010年

2 蔣丹;無線傳感器網(wǎng)絡(luò)覆蓋盲區(qū)的發(fā)現(xiàn)與修復(fù)方法研究[D];東北大學(xué);2008年

，

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