本文選題：無線傳感器網(wǎng)絡(luò)　切入點(diǎn)：節(jié)點(diǎn)定位算法　出處：《中國礦業(yè)大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：無線傳感器網(wǎng)絡(luò)(Wireless Sensor Network,WSN)是一門集中了嵌入式技術(shù)、微電子技術(shù)、傳感器技術(shù)、分布式信息處理技術(shù)和通信網(wǎng)絡(luò)等技術(shù)的交叉學(xué)科,在環(huán)境監(jiān)測(cè)、醫(yī)療衛(wèi)生、國防軍事、交通管理等領(lǐng)域具有廣闊的應(yīng)用前景�，F(xiàn)有應(yīng)用大都需要預(yù)先獲知傳感器節(jié)點(diǎn)的位置,沒有位置信息的監(jiān)測(cè)數(shù)據(jù)往往毫無意義。因此,對(duì)無線傳感器網(wǎng)絡(luò)節(jié)點(diǎn)定位的研究具有重要意義。首先,本文從信號(hào)相似性出發(fā),提出一種基于信號(hào)相似性的無線傳感器網(wǎng)絡(luò)節(jié)點(diǎn)定位算法。該方法通過比較兩個(gè)鄰居節(jié)點(diǎn)接收到其它節(jié)點(diǎn)發(fā)送來信號(hào)的相似性,計(jì)算這兩個(gè)節(jié)點(diǎn)間的相對(duì)距離。使用最短路徑算法計(jì)算非鄰居節(jié)點(diǎn)間的相對(duì)距離后得到整個(gè)網(wǎng)絡(luò)的相對(duì)距離圖。在已知至少3個(gè)錨節(jié)點(diǎn)位置的前提下,利用MDS算法計(jì)算出節(jié)點(diǎn)的物理位置。其次,在信號(hào)相似性基礎(chǔ)上,結(jié)合結(jié)構(gòu)相似性,提出一種融合結(jié)構(gòu)相似性的無線傳感器網(wǎng)絡(luò)節(jié)點(diǎn)定位算法。首先,根據(jù)傳感器節(jié)點(diǎn)是否能夠通信生成一個(gè)網(wǎng)絡(luò)拓?fù)鋱D。然后計(jì)算任意兩個(gè)節(jié)點(diǎn)之間信號(hào)相似性值作為拓?fù)鋱D邊的權(quán)值。使用基于加權(quán)SimRank算法計(jì)算兩個(gè)節(jié)點(diǎn)之間的結(jié)構(gòu)相似度并作為相對(duì)距離。最后,在已知至少3個(gè)錨節(jié)點(diǎn)位置的前提下,使用MDS算法完成對(duì)未知節(jié)點(diǎn)的定位。最后,分別在規(guī)則的和非規(guī)則的無線傳感器網(wǎng)絡(luò)中對(duì)本文所提出的兩種算法進(jìn)行了實(shí)驗(yàn)驗(yàn)證,結(jié)果表明,本文提出的兩種基于相似性的無線傳感器網(wǎng)絡(luò)節(jié)點(diǎn)定位算法具有較好的定位精度。
[Abstract]:Wireless Sensor Network (WSNs) is an interdisciplinary subject that focuses on embedded technology, microelectronics, sensor technology, distributed information processing technology and communication network, in environmental monitoring, health care, national defense, military affairs, etc. Most of the existing applications need to know the location of sensor nodes in advance, and monitoring data without location information are often meaningless. The research on node localization in wireless sensor networks is of great significance. Firstly, this paper starts from the similarity of signals. A node localization algorithm based on signal similarity in wireless sensor networks is proposed, which compares the similarity of signals sent by two neighbor nodes to other nodes. The relative distance between the two nodes is calculated. The relative distance graph of the whole network is obtained by using the shortest path algorithm to calculate the relative distance between the non-neighbor nodes. The physical location of nodes is calculated by using MDS algorithm. Secondly, based on the similarity of signals and structural similarity, a node location algorithm based on structural similarity in wireless sensor networks is proposed. A network topology graph is generated according to whether the sensor node can communicate. Then the similarity value of the signal between any two nodes is calculated as the weight of the edge of the topology graph. Based on the weighted SimRank algorithm, the junction between the two nodes is calculated. Construct the similarity and act as the relative distance. Finally, Under the condition that at least three anchor nodes are known, MDS algorithm is used to locate the unknown nodes. Finally, the two algorithms proposed in this paper are experimentally verified in both regular and irregular wireless sensor networks. The results show that the proposed two similarity based node localization algorithms in wireless sensor networks have good localization accuracy.
【學(xué)位授予單位】：中國礦業(yè)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

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