本文選題：無線傳感器網絡 + 分簇拓撲��； 參考：《鄭州大學》2017年碩士論文

【摘要】：無線傳感器網絡(Wireless Sensor Network,WSN)是一項多種學科技術高度交叉的綜合性前沿研究領域,受到社會各界的高度重視。鑒于WSN能量受限及多跳等特點,使得WSN路由協(xié)議成為WSN研究領域的難點。分層路由由于其低能耗且易擴展的特性已成為WSN路由協(xié)議的研究重點,而分簇拓撲技術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關的分簇拓撲算法(a Hierarchical Clustering Algorithm based on Gradient with Gateway,HCAGG)。該算法綜合考慮節(jié)點的剩余能量和平均距離兩項因素選取簇頭;在建立簇樹階段,網關節(jié)點的引入有效降低了較遠簇頭間直接通信的高能耗。但是該算法在簇頭選舉時未考慮簇內節(jié)點能量的分布,而網關節(jié)點的選取過分依賴于梯度。針對HCAGG算法中存在的問題,本文提出一種基于改進粒子群優(yōu)化算法的分簇拓撲算法(a Clustering Topology based on Modified Particle Swarm Optimization,CTMPSO)。針對PSO算法易早熟收斂的缺點,首先提出一種改進粒子群優(yōu)化算法MPSO,該算法引入人工魚群算法中的視野及隨機行為,增強粒子搜尋的多樣性,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)驗證了該MPSO算法的有效性。同時,結合WSN及MPSO算法特點,構建多局部最優(yōu)覓食場景及適合離散WSN環(huán)境的連續(xù)評價函數(shù),使MPSO算法更好的應用于WSN。此外,針對待優(yōu)化目標特點,采用比較法逐步確定搜索區(qū)域。針對HCAGG中簇頭的問題,綜合考慮鄰居節(jié)點剩余能量、到節(jié)點的平均距離以及簇內能量分布重新構建適應度函數(shù),利用MPSO算法搜尋最佳節(jié)點擔任新簇頭。針對HCAGG中網關的問題,提出一種兩跳內最優(yōu)網關并結合MPSO算法對網關進行優(yōu)化。實驗結果表明,該CTMPSO算法能顯著延長全網的存活期。最后給出CTMPSO算法節(jié)點上、下線的維護與更新策略,以提高算法的自適應性。同時,針對WSN新興領域中要求節(jié)點移動的場景,給出CTMPSO算法移動情況下的維護更新策略,擴大算法的應用領域。
[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.
【學位授予單位】：鄭州大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TN929.5;TP212.9

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