基于拓?fù)淇刂频奈锫?lián)網(wǎng)優(yōu)化技術(shù)研究
發(fā)布時(shí)間：2018-06-13 23:49
本文選題：物聯(lián)網(wǎng) + 拓?fù)淇刂?/strong>��； 參考：《安徽理工大學(xué)》2017年碩士論文
【摘要】：隨著科技的進(jìn)步,經(jīng)濟(jì)的發(fā)展,物聯(lián)網(wǎng)已經(jīng)成為當(dāng)今研究的熱點(diǎn),由于其功能強(qiáng)大以及很好的智能性,已經(jīng)成為生活中不可或缺的一部分。因?yàn)槲锫?lián)網(wǎng)技術(shù)可以自動(dòng)的獲取周?chē)男畔?這就使得網(wǎng)絡(luò)節(jié)點(diǎn)在其扮演著中重要角色。網(wǎng)絡(luò)節(jié)點(diǎn)一般都是大規(guī)模的組成一個(gè)拓?fù)浣Y(jié)構(gòu),要想網(wǎng)絡(luò)的生存時(shí)間長(zhǎng),這就要求網(wǎng)絡(luò)拓?fù)浣Y(jié)構(gòu)應(yīng)該設(shè)計(jì)的更加合理,也就是設(shè)計(jì)出能耗低的拓?fù)浣Y(jié)構(gòu)。所以一個(gè)性能更佳以及能量損耗更低的網(wǎng)絡(luò)拓?fù)浣Y(jié)構(gòu)是當(dāng)前重要的研究目標(biāo)。本文主要對(duì)物聯(lián)網(wǎng)中網(wǎng)絡(luò)拓?fù)浣Y(jié)構(gòu)進(jìn)行了分析和研究,對(duì)已有的算法進(jìn)行改進(jìn),提出了基于遺傳算法對(duì)LEACH拓?fù)渌惴ǖ膬?yōu)化(LEACH-GA)。LEACH-GA算法在簇頭選取的階段,通過(guò)對(duì)閥值的修改,使得簇頭的選擇考慮的因素包括簇頭的剩余能量、節(jié)點(diǎn)的鄰居節(jié)點(diǎn)數(shù)以及節(jié)點(diǎn)是否當(dāng)選過(guò)簇頭等,這樣選擇出來(lái)的簇頭會(huì)更加合理;另外在簇的建立階段,利用遺傳算法的適應(yīng)度函數(shù)的計(jì)算值來(lái)確定更加合理的分簇結(jié)構(gòu)。通過(guò)MATLAB仿真表明,改進(jìn)后的算法在節(jié)點(diǎn)的生命周期以及數(shù)據(jù)發(fā)送量都有所提高,說(shuō)明改進(jìn)后的算法網(wǎng)絡(luò)結(jié)構(gòu)更加合理。本文結(jié)合網(wǎng)絡(luò)節(jié)點(diǎn)以及提出的算法,設(shè)計(jì)出能夠?qū)崿F(xiàn)LEACH-GA算法的硬件電路,利用FPGA芯片來(lái)實(shí)現(xiàn)算法。實(shí)驗(yàn)結(jié)果表明LEACH-GA算法確實(shí)能夠提高物聯(lián)網(wǎng)中網(wǎng)絡(luò)拓?fù)浣Y(jié)構(gòu)的能量利用率,從而延長(zhǎng)物聯(lián)網(wǎng)的網(wǎng)絡(luò)生存時(shí)間。
[Abstract]:With the progress of science and technology and the development of economy, the Internet of things has become a hot spot of research today, because of its powerful function and good intelligence, it has become an indispensable part of life. Because the Internet of things technology can automatically obtain the surrounding information, this makes network nodes play an important role in it. Network nodes generally constitute a topology structure on a large scale. In order to live a long time, network topology should be designed more reasonably, that is, to design a topology with low energy consumption. Therefore, a network topology with better performance and lower energy loss is an important research goal. In this paper, the network topology in the Internet of things is analyzed and studied, the existing algorithms are improved, and the optimization of Leach topology algorithm based on genetic algorithm is proposed. In the stage of cluster head selection, the threshold is modified. The factors that make the cluster head selection consider include the residual energy of the cluster head, the number of neighbor nodes of the node and whether the node has been elected as the cluster head, so that the selected cluster head will be more reasonable; in addition, in the stage of cluster establishment, A more reasonable clustering structure is determined by using the computational value of fitness function of genetic algorithm. The MATLAB simulation shows that the improved algorithm can improve the node life cycle and data delivery, which indicates that the improved algorithm network structure is more reasonable. Combining the network node and the proposed algorithm, this paper designs the hardware circuit which can realize the LEACH-GA algorithm, and uses FPGA chip to realize the algorithm. The experimental results show that the LEACH-GA algorithm can improve the energy utilization rate of the network topology in the Internet of things, thus prolonging the network lifetime of the Internet of things.
【學(xué)位授予單位】：安徽理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TP391.44;TN929.5
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