基于認知的移動Ad Hoc網(wǎng)絡重構推理決策技術
發(fā)布時間：2018-09-11 06:15
【摘要】：認知移動自組織網(wǎng)絡是由多個地位相等的移動節(jié)點所構成的認知網(wǎng)絡,是移動自組織網(wǎng)絡技術與認知網(wǎng)絡技術的結合。認知網(wǎng)絡的智能性主要體現(xiàn)在其重構能力上,網(wǎng)絡重構技術使網(wǎng)絡能夠根據(jù)內外部環(huán)境條件變化導致的網(wǎng)絡狀態(tài)的變化,動態(tài)優(yōu)化配置網(wǎng)絡結構和網(wǎng)絡協(xié)議,提高網(wǎng)絡通信性能。隨著無線通信網(wǎng)絡的不斷發(fā)展,用戶對認知網(wǎng)絡的要求越來越高,作為認知網(wǎng)絡的關鍵技術之一,網(wǎng)絡重構技術以其重要性和不可或缺性逐漸得到了大家的重視,已成為認知網(wǎng)絡的一大研究重點。目前的網(wǎng)絡重構技術研究并沒有形成體系,還沒有完全覆蓋到重構實現(xiàn)的方方面面,基本上分布在幾個細節(jié)的研究點上面。認知移動自組織網(wǎng)絡的重構技術的研究尚處于初始階段,研究內容主要集中在基于認知信息的各層協(xié)議的優(yōu)化設計上。本文研究網(wǎng)絡重構技術在認知移動自組織網(wǎng)絡中的應用和操作,在已有相關文獻的研究基礎上,主要研究網(wǎng)絡參數(shù)重構和路由協(xié)議重構。本文的研究內容主要分為以下幾個部分:首先,基于網(wǎng)絡參數(shù)的多樣性,對移動Ad Hoc網(wǎng)絡的參數(shù)進行了分類,并詳細介紹了不同場景下的網(wǎng)絡參數(shù)的選取方法。其次,由于網(wǎng)絡重構本質上是一個多目標優(yōu)化問題,詳細介紹了優(yōu)化目標函數(shù)的構建方法,包括各性能參數(shù)效用函數(shù)的構建和多指標合成模型的選取。然后,提出了一種基于貝葉斯網(wǎng)絡、遺傳算法和案例推理的網(wǎng)絡參數(shù)重構算法,包括在某些代表性網(wǎng)絡場景下基于貝葉斯網(wǎng)絡和遺傳算法的策略知識庫的構建方法和在新的網(wǎng)絡場景下基于案例推理的重構推理決策方法,參數(shù)重構通過協(xié)議參數(shù)的動態(tài)調整實現(xiàn)網(wǎng)絡對動態(tài)環(huán)境的適應性,仿真結果證明參數(shù)重構算法的運用能在動態(tài)環(huán)境中提升網(wǎng)絡性能,包括端到端時延、網(wǎng)絡吞吐量和分組遞交率。最后,提出了一種基于自適應神經(jīng)模糊推理系統(tǒng)的路由協(xié)議重構算法,通過建立路由協(xié)議性能行為模型實現(xiàn)不同網(wǎng)絡場景下選擇不同路由協(xié)議的目標,保證網(wǎng)絡在動態(tài)環(huán)境中的通信性能,仿真結果表明路由協(xié)議重構算法使網(wǎng)絡能夠基于網(wǎng)絡場景選擇能提供最優(yōu)通信性能的路由協(xié)議,從而驗證了算法的有效性。
[Abstract]:Cognitive mobile ad hoc network is a cognitive network composed of multiple mobile nodes of equal status. It is the combination of mobile ad hoc network technology and cognitive network technology. The intelligence of cognitive network is mainly reflected in its reconfiguration ability. Network reconfiguration technology enables the network to dynamically optimize network structure and network protocol according to the changes of network state caused by the changes of internal and external environment conditions. Improve network communication performance. With the development of wireless communication network, users are demanding more and more cognitive network. As one of the key technologies of cognitive network, network reconfiguration technology has been paid more and more attention for its importance and necessity. Has become a major research focus of cognitive networks. The current network reconfiguration technology research has not formed the system, has not completely covered all aspects of the implementation of the reconfiguration, basically distributed in several details of the research points. The research on the reconstruction of cognitive mobile ad hoc networks is still in the initial stage, and the research focuses on the optimization design of the protocols based on cognitive information. In this paper, the application and operation of network reconfiguration in cognitive mobile ad hoc networks are studied. Based on the existing literatures, the network parameter reconfiguration and routing protocol reconfiguration are studied. The main research contents of this paper are as follows: firstly, based on the diversity of network parameters, the parameters of mobile Ad Hoc network are classified, and the selection methods of network parameters under different scenarios are introduced in detail. Secondly, because network reconfiguration is essentially a multi-objective optimization problem, the construction method of optimization objective function is introduced in detail, including the construction of utility function of each performance parameter and the selection of multi-index composite model. Then, a network parameter reconstruction algorithm based on Bayesian network, genetic algorithm and case-based reasoning is proposed. It includes the method of constructing the strategy knowledge base based on Bayesian network and genetic algorithm in some representative network scenarios and the method of reconstructing reasoning decision based on case-based reasoning in the new network scenario. Parameter reconstruction realizes the adaptability of network to dynamic environment through dynamic adjustment of protocol parameters. Simulation results show that the application of parameter reconstruction algorithm can improve network performance in dynamic environment, including end-to-end delay. Network throughput and packet delivery rate. Finally, a routing protocol reconfiguration algorithm based on adaptive neural fuzzy inference system is proposed. The routing protocol performance behavior model is established to achieve the goal of selecting different routing protocols in different network scenarios. The simulation results show that the routing protocol reconfiguration algorithm enables the network to select the routing protocol which can provide the optimal communication performance based on the network scenario, thus validating the effectiveness of the algorithm.
【學位授予單位】：電子科技大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TN929.5
本文編號：2235853
[Abstract]:Cognitive mobile ad hoc network is a cognitive network composed of multiple mobile nodes of equal status. It is the combination of mobile ad hoc network technology and cognitive network technology. The intelligence of cognitive network is mainly reflected in its reconfiguration ability. Network reconfiguration technology enables the network to dynamically optimize network structure and network protocol according to the changes of network state caused by the changes of internal and external environment conditions. Improve network communication performance. With the development of wireless communication network, users are demanding more and more cognitive network. As one of the key technologies of cognitive network, network reconfiguration technology has been paid more and more attention for its importance and necessity. Has become a major research focus of cognitive networks. The current network reconfiguration technology research has not formed the system, has not completely covered all aspects of the implementation of the reconfiguration, basically distributed in several details of the research points. The research on the reconstruction of cognitive mobile ad hoc networks is still in the initial stage, and the research focuses on the optimization design of the protocols based on cognitive information. In this paper, the application and operation of network reconfiguration in cognitive mobile ad hoc networks are studied. Based on the existing literatures, the network parameter reconfiguration and routing protocol reconfiguration are studied. The main research contents of this paper are as follows: firstly, based on the diversity of network parameters, the parameters of mobile Ad Hoc network are classified, and the selection methods of network parameters under different scenarios are introduced in detail. Secondly, because network reconfiguration is essentially a multi-objective optimization problem, the construction method of optimization objective function is introduced in detail, including the construction of utility function of each performance parameter and the selection of multi-index composite model. Then, a network parameter reconstruction algorithm based on Bayesian network, genetic algorithm and case-based reasoning is proposed. It includes the method of constructing the strategy knowledge base based on Bayesian network and genetic algorithm in some representative network scenarios and the method of reconstructing reasoning decision based on case-based reasoning in the new network scenario. Parameter reconstruction realizes the adaptability of network to dynamic environment through dynamic adjustment of protocol parameters. Simulation results show that the application of parameter reconstruction algorithm can improve network performance in dynamic environment, including end-to-end delay. Network throughput and packet delivery rate. Finally, a routing protocol reconfiguration algorithm based on adaptive neural fuzzy inference system is proposed. The routing protocol performance behavior model is established to achieve the goal of selecting different routing protocols in different network scenarios. The simulation results show that the routing protocol reconfiguration algorithm enables the network to select the routing protocol which can provide the optimal communication performance based on the network scenario, thus validating the effectiveness of the algorithm.
【學位授予單位】：電子科技大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TN929.5
【共引文獻】
相關期刊論文 前1條
1 柴爭義;王秉;李亞倫;朱思峰;王穎鋒;;擬態(tài)物理學多目標算法求解認知參數(shù)優(yōu)化問題[J];電子學報;2015年08期
相關博士學位論文 前5條
1 賀倩;認知無線網(wǎng)絡中的重構管理研究[D];北京郵電大學;2013年
2 周明月;認知無線電系統(tǒng)的資源分配問題研究[D];吉林大學;2014年
3 王士顯;面向認知無線電的數(shù)字信號處理器體系結構技術研究[D];國防科學技術大學;2013年
4 伍春;認知無線電中智能學習技術研究[D];西安電子科技大學;2014年
5 王欽輝;認知無線網(wǎng)絡中誠信頻譜拍賣機制研究[D];南京大學;2015年
相關碩士學位論文 前1條
1 李明智;嵌入式移動數(shù)據(jù)庫數(shù)據(jù)同步技術的研究[D];浙江海洋學院;2014年
，本文編號：2235853
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