WSN中基于改進(jìn)粒子群優(yōu)化算法的分簇拓?fù)渌惴ㄑ芯?/H1>
發(fā)布時(shí)間：2018-04-12 22:07
本文選題：無線傳感器網(wǎng)絡(luò) + 分簇拓?fù)?/strong>��； 參考：《鄭州大學(xué)》2017年碩士論文
【摘要】：無線傳感器網(wǎng)絡(luò)(Wireless Sensor Network,WSN)是一項(xiàng)多種學(xué)科技術(shù)高度交叉的綜合性前沿研究領(lǐng)域,受到社會(huì)各界的高度重視。鑒于WSN能量受限及多跳等特點(diǎn),使得WSN路由協(xié)議成為WSN研究領(lǐng)域的難點(diǎn)。分層路由由于其低能耗且易擴(kuò)展的特性已成為WSN路由協(xié)議的研究重點(diǎn),而分簇拓?fù)浼夹g(shù)作為分層路由的重要部分,亦備受重視。本文首先介紹一種基于梯度的有網(wǎng)關(guān)的分簇拓?fù)渌惴?a Hierarchical Clustering Algorithm based on Gradient with Gateway,HCAGG)。該算法綜合考慮節(jié)點(diǎn)的剩余能量和平均距離兩項(xiàng)因素選取簇頭;在建立簇樹階段,網(wǎng)關(guān)節(jié)點(diǎn)的引入有效降低了較遠(yuǎn)簇頭間直接通信的高能耗。但是該算法在簇頭選舉時(shí)未考慮簇內(nèi)節(jié)點(diǎn)能量的分布,而網(wǎng)關(guān)節(jié)點(diǎn)的選取過分依賴于梯度。針對(duì)HCAGG算法中存在的問題,本文提出一種基于改進(jìn)粒子群優(yōu)化算法的分簇拓?fù)渌惴?a Clustering Topology based on Modified Particle Swarm Optimization,CTMPSO)。針對(duì)PSO算法易早熟收斂的缺點(diǎn),首先提出一種改進(jìn)粒子群優(yōu)化算法MPSO,該算法引入人工魚群算法中的視野及隨機(jī)行為,增強(qiáng)粒子搜尋的多樣性,避免粒子過早陷入局部最優(yōu),并通過Sphere函數(shù)和Ratrigrin函數(shù)驗(yàn)證了該MPSO算法的有效性。同時(shí),結(jié)合WSN及MPSO算法特點(diǎn),構(gòu)建多局部最優(yōu)覓食場(chǎng)景及適合離散WSN環(huán)境的連續(xù)評(píng)價(jià)函數(shù),使MPSO算法更好的應(yīng)用于WSN。此外,針對(duì)待優(yōu)化目標(biāo)特點(diǎn),采用比較法逐步確定搜索區(qū)域。針對(duì)HCAGG中簇頭的問題,綜合考慮鄰居節(jié)點(diǎn)剩余能量、到節(jié)點(diǎn)的平均距離以及簇內(nèi)能量分布重新構(gòu)建適應(yīng)度函數(shù),利用MPSO算法搜尋最佳節(jié)點(diǎn)擔(dān)任新簇頭。針對(duì)HCAGG中網(wǎng)關(guān)的問題,提出一種兩跳內(nèi)最優(yōu)網(wǎng)關(guān)并結(jié)合MPSO算法對(duì)網(wǎng)關(guān)進(jìn)行優(yōu)化。實(shí)驗(yàn)結(jié)果表明,該CTMPSO算法能顯著延長全網(wǎng)的存活期。最后給出CTMPSO算法節(jié)點(diǎn)上、下線的維護(hù)與更新策略,以提高算法的自適應(yīng)性。同時(shí),針對(duì)WSN新興領(lǐng)域中要求節(jié)點(diǎn)移動(dòng)的場(chǎng)景,給出CTMPSO算法移動(dòng)情況下的維護(hù)更新策略,擴(kuò)大算法的應(yīng)用領(lǐng)域。
[Abstract]:Wireless Sensor Network (WSNs) is a comprehensive frontier research field, which is highly intersected by many disciplines and technologies, and is highly valued by all walks of life.Due to the characteristics of WSN energy limitation and multi-hop, WSN routing protocol becomes a difficult problem in the field of WSN research.Because of its low energy consumption and easy to extend, hierarchical routing has become the focus of WSN routing protocols. As an important part of hierarchical routing, clustering topology has been paid more attention.In this paper, we first introduce a Hierarchical Clustering Algorithm based on Gradient with Gateway-HCAGG algorithm based on gradients with gateways.The algorithm considers both residual energy and average distance of nodes to select cluster heads. In the stage of building cluster tree, the introduction of gateway node can effectively reduce the high energy consumption of direct communication between remote cluster heads.However, the algorithm does not consider the energy distribution of the nodes in the cluster when the cluster head is elected, and the selection of the gateway nodes is too dependent on the gradient.Aiming at the problems in HCAGG algorithm, this paper presents a Clustering Topology based on Modified Particle Swarm optimization algorithm based on improved particle swarm optimization (PSO) algorithm.In order to overcome the disadvantage of premature convergence of PSO algorithm, an improved particle swarm optimization algorithm (MPSOs) is proposed. The algorithm introduces the field of vision and random behavior of artificial fish swarm algorithm to enhance the diversity of particle search, and to avoid the particle falling into local optimum prematurely.The validity of the MPSO algorithm is verified by Sphere function and Ratrigrin function.At the same time, combined with the characteristics of WSN and MPSO algorithm, the multi-local optimal foraging scene and the continuous evaluation function suitable for discrete WSN environment are constructed, so that the MPSO algorithm can be applied to WSN better.In addition, according to the characteristics of the target to be optimized, the search area is determined step by step by comparison method.Considering the residual energy of neighbor nodes, the average distance to the nodes and the energy distribution within the cluster, the fitness function is reconstructed to solve the cluster head problem in HCAGG, and the MPSO algorithm is used to search for the best node as the new cluster head.Aiming at the problem of gateway in HCAGG, this paper presents a two-hop optimal gateway and optimizes the gateway with MPSO algorithm.Experimental results show that the CTMPSO algorithm can significantly prolong the lifetime of the whole network.Finally, the maintenance and update strategy of the CTMPSO algorithm node is given to improve the adaptability of the algorithm.At the same time, aiming at the scene of node moving in the emerging field of WSN, the maintenance and update strategy of CTMPSO algorithm is given to expand the application field of the algorithm.
【學(xué)位授予單位】：鄭州大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TN929.5;TP212.9
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1 王衛(wèi)紅;林玉炳;陳鐵明;;橢圓曲線密碼體制在WSN上的應(yīng)用[J];計(jì)算機(jī)工程;2009年16期
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本文編號(hào)：1741626
本文鏈接：http://www.wukwdryxk.cn/shoufeilunwen/xixikjs/1741626.html
本文選題：無線傳感器網(wǎng)絡(luò) + 分簇拓?fù)?/strong>��； 參考：《鄭州大學(xué)》2017年碩士論文
【摘要】：無線傳感器網(wǎng)絡(luò)(Wireless Sensor Network,WSN)是一項(xiàng)多種學(xué)科技術(shù)高度交叉的綜合性前沿研究領(lǐng)域,受到社會(huì)各界的高度重視。鑒于WSN能量受限及多跳等特點(diǎn),使得WSN路由協(xié)議成為WSN研究領(lǐng)域的難點(diǎn)。分層路由由于其低能耗且易擴(kuò)展的特性已成為WSN路由協(xié)議的研究重點(diǎn),而分簇拓?fù)浼夹g(shù)作為分層路由的重要部分,亦備受重視。本文首先介紹一種基于梯度的有網(wǎng)關(guān)的分簇拓?fù)渌惴?a Hierarchical Clustering Algorithm based on Gradient with Gateway,HCAGG)。該算法綜合考慮節(jié)點(diǎn)的剩余能量和平均距離兩項(xiàng)因素選取簇頭;在建立簇樹階段,網(wǎng)關(guān)節(jié)點(diǎn)的引入有效降低了較遠(yuǎn)簇頭間直接通信的高能耗。但是該算法在簇頭選舉時(shí)未考慮簇內(nèi)節(jié)點(diǎn)能量的分布,而網(wǎng)關(guān)節(jié)點(diǎn)的選取過分依賴于梯度。針對(duì)HCAGG算法中存在的問題,本文提出一種基于改進(jìn)粒子群優(yōu)化算法的分簇拓?fù)渌惴?a Clustering Topology based on Modified Particle Swarm Optimization,CTMPSO)。針對(duì)PSO算法易早熟收斂的缺點(diǎn),首先提出一種改進(jìn)粒子群優(yōu)化算法MPSO,該算法引入人工魚群算法中的視野及隨機(jī)行為,增強(qiáng)粒子搜尋的多樣性,避免粒子過早陷入局部最優(yōu),并通過Sphere函數(shù)和Ratrigrin函數(shù)驗(yàn)證了該MPSO算法的有效性。同時(shí),結(jié)合WSN及MPSO算法特點(diǎn),構(gòu)建多局部最優(yōu)覓食場(chǎng)景及適合離散WSN環(huán)境的連續(xù)評(píng)價(jià)函數(shù),使MPSO算法更好的應(yīng)用于WSN。此外,針對(duì)待優(yōu)化目標(biāo)特點(diǎn),采用比較法逐步確定搜索區(qū)域。針對(duì)HCAGG中簇頭的問題,綜合考慮鄰居節(jié)點(diǎn)剩余能量、到節(jié)點(diǎn)的平均距離以及簇內(nèi)能量分布重新構(gòu)建適應(yīng)度函數(shù),利用MPSO算法搜尋最佳節(jié)點(diǎn)擔(dān)任新簇頭。針對(duì)HCAGG中網(wǎng)關(guān)的問題,提出一種兩跳內(nèi)最優(yōu)網(wǎng)關(guān)并結(jié)合MPSO算法對(duì)網(wǎng)關(guān)進(jìn)行優(yōu)化。實(shí)驗(yàn)結(jié)果表明,該CTMPSO算法能顯著延長全網(wǎng)的存活期。最后給出CTMPSO算法節(jié)點(diǎn)上、下線的維護(hù)與更新策略,以提高算法的自適應(yīng)性。同時(shí),針對(duì)WSN新興領(lǐng)域中要求節(jié)點(diǎn)移動(dòng)的場(chǎng)景,給出CTMPSO算法移動(dòng)情況下的維護(hù)更新策略,擴(kuò)大算法的應(yīng)用領(lǐng)域。
[Abstract]:Wireless Sensor Network (WSNs) is a comprehensive frontier research field, which is highly intersected by many disciplines and technologies, and is highly valued by all walks of life.Due to the characteristics of WSN energy limitation and multi-hop, WSN routing protocol becomes a difficult problem in the field of WSN research.Because of its low energy consumption and easy to extend, hierarchical routing has become the focus of WSN routing protocols. As an important part of hierarchical routing, clustering topology has been paid more attention.In this paper, we first introduce a Hierarchical Clustering Algorithm based on Gradient with Gateway-HCAGG algorithm based on gradients with gateways.The algorithm considers both residual energy and average distance of nodes to select cluster heads. In the stage of building cluster tree, the introduction of gateway node can effectively reduce the high energy consumption of direct communication between remote cluster heads.However, the algorithm does not consider the energy distribution of the nodes in the cluster when the cluster head is elected, and the selection of the gateway nodes is too dependent on the gradient.Aiming at the problems in HCAGG algorithm, this paper presents a Clustering Topology based on Modified Particle Swarm optimization algorithm based on improved particle swarm optimization (PSO) algorithm.In order to overcome the disadvantage of premature convergence of PSO algorithm, an improved particle swarm optimization algorithm (MPSOs) is proposed. The algorithm introduces the field of vision and random behavior of artificial fish swarm algorithm to enhance the diversity of particle search, and to avoid the particle falling into local optimum prematurely.The validity of the MPSO algorithm is verified by Sphere function and Ratrigrin function.At the same time, combined with the characteristics of WSN and MPSO algorithm, the multi-local optimal foraging scene and the continuous evaluation function suitable for discrete WSN environment are constructed, so that the MPSO algorithm can be applied to WSN better.In addition, according to the characteristics of the target to be optimized, the search area is determined step by step by comparison method.Considering the residual energy of neighbor nodes, the average distance to the nodes and the energy distribution within the cluster, the fitness function is reconstructed to solve the cluster head problem in HCAGG, and the MPSO algorithm is used to search for the best node as the new cluster head.Aiming at the problem of gateway in HCAGG, this paper presents a two-hop optimal gateway and optimizes the gateway with MPSO algorithm.Experimental results show that the CTMPSO algorithm can significantly prolong the lifetime of the whole network.Finally, the maintenance and update strategy of the CTMPSO algorithm node is given to improve the adaptability of the algorithm.At the same time, aiming at the scene of node moving in the emerging field of WSN, the maintenance and update strategy of CTMPSO algorithm is given to expand the application field of the algorithm.
【學(xué)位授予單位】：鄭州大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TN929.5;TP212.9
【相似文獻(xiàn)】
相關(guān)期刊論文 前10條
1 王衛(wèi)紅;林玉炳;陳鐵明;;橢圓曲線密碼體制在WSN上的應(yīng)用[J];計(jì)算機(jī)工程;2009年16期
2 劉貞;丁明理;王祁;;WSN多節(jié)點(diǎn)決策信息融合在機(jī)器人自主導(dǎo)航中的應(yīng)用[J];電子學(xué)報(bào);2008年12期
3 王培東;梁麗麗;叢軼姝;;基于改進(jìn)遺傳模擬退火算法的WSN路徑優(yōu)化[J];微型機(jī)與應(yīng)用;2011年07期
4 朱偉龍;陳傳峰;;WSN安全通信的形式化驗(yàn)證[J];信息安全與通信保密;2013年04期
5 韓明軍;熊焰;陸琦瑋;龔旭東;劉濤;;無人值守WSN中基于中國剩余定理的可靠數(shù)據(jù)生存方案[J];計(jì)算機(jī)應(yīng)用;2013年05期
6 金紅;蔣存波;項(xiàng)春雷;陳麗虹;;一種融合WSN的現(xiàn)場(chǎng)總線控制系統(tǒng)多協(xié)議控制器[J];計(jì)算機(jī)測(cè)量與控制;2014年03期
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8 鄧延安;沈連豐;;WSN中運(yùn)動(dòng)物體監(jiān)測(cè)的節(jié)點(diǎn)控制策略[J];計(jì)算機(jī)工程;2009年14期
9 陶昆;吳艦;;WSN在花卉大棚中的應(yīng)用研究[J];自動(dòng)化與儀器儀表;2011年05期
10 周捷;郭淵博;胡凌燕;;WSN中針對(duì)節(jié)點(diǎn)捕獲攻擊的檢測(cè)與控制[J];西安電子科技大學(xué)學(xué)報(bào);2012年01期
相關(guān)會(huì)議論文 前10條
1 灻宏P(guān)I;_5PI;;WSN在城市地，
本文編號(hào)：1741626
本文鏈接：http://www.wukwdryxk.cn/shoufeilunwen/xixikjs/1741626.html
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