本文關(guān)鍵詞： 無(wú)線(xiàn)監(jiān)測(cè)網(wǎng)絡(luò) QoM 信道選擇 粒子群優(yōu)化 蒙特卡洛 TDMA時(shí)隙 調(diào)度 頂點(diǎn)著色 網(wǎng)絡(luò)沖突 序列學(xué)習(xí) 仿真軟件　出處：《合肥工業(yè)大學(xué)》2016年博士論文　論文類(lèi)型：學(xué)位論文

【摘要】：隨著無(wú)線(xiàn)網(wǎng)絡(luò)規(guī)模的擴(kuò)大和應(yīng)用的豐富,網(wǎng)絡(luò)的性能保障、安全性和穩(wěn)定性等面臨越來(lái)越大的挑戰(zhàn)。在無(wú)線(xiàn)網(wǎng)絡(luò)中采用多個(gè)無(wú)線(xiàn)嗅探器(sniffer)實(shí)時(shí)收集用戶(hù)傳輸?shù)臄?shù)據(jù),可以實(shí)現(xiàn)無(wú)線(xiàn)網(wǎng)絡(luò)的故障診斷和資源管理,對(duì)提升網(wǎng)絡(luò)性能、保障網(wǎng)絡(luò)安全、改善用戶(hù)體驗(yàn)等具有重要意義。由于sniffer數(shù)量有限,因此如何優(yōu)化各個(gè)sniffer的硬件配置和軟件調(diào)度,使它們覆蓋最多的網(wǎng)絡(luò)用戶(hù),獲取最多的網(wǎng)絡(luò)數(shù)據(jù),從而最大化網(wǎng)絡(luò)監(jiān)測(cè)質(zhì)量(Quality of Monitoring, QoM)成為了當(dāng)今的熱點(diǎn)課題之一。該文全面總結(jié)了無(wú)線(xiàn)監(jiān)測(cè)網(wǎng)絡(luò)優(yōu)化QOM的理論和技術(shù)現(xiàn)狀,重點(diǎn)研究了優(yōu)化sniffer的信道分配/選擇以提高QOM的方法和算法,并通過(guò)理論推導(dǎo)、仿真與實(shí)際測(cè)試證明了所提出方法的有效性。本文的主要研究工作及創(chuàng)新之處在于：(1)總結(jié)了無(wú)線(xiàn)監(jiān)測(cè)網(wǎng)絡(luò)的概念和研究現(xiàn)狀�？偨Y(jié)了無(wú)線(xiàn)監(jiān)測(cè)網(wǎng)絡(luò)的定義、分類(lèi)和系統(tǒng)框架等；討論了無(wú)線(xiàn)監(jiān)測(cè)網(wǎng)絡(luò)優(yōu)化QOM的方法,重點(diǎn)介紹了通過(guò)優(yōu)化sniffer的信道分配/選擇提高QOM的各種模型和方法,并從多種性能評(píng)價(jià)指標(biāo)出發(fā)對(duì)現(xiàn)有方法進(jìn)行了分析和比較；論述了無(wú)線(xiàn)監(jiān)測(cè)網(wǎng)絡(luò)優(yōu)化QOM有待解決的關(guān)鍵問(wèn)題,以及本文的研究思路和安排。(2)針對(duì)無(wú)線(xiàn)監(jiān)測(cè)網(wǎng)絡(luò)數(shù)據(jù)收集過(guò)程中的sniffer信道選擇問(wèn)題,提出了一種蒙特卡洛增強(qiáng)粒子群優(yōu)化的sniffer信道選擇算法。設(shè)計(jì)了二維映射粒子編碼和相應(yīng)的移動(dòng)方案,并引入蒙特卡洛方法來(lái)修正解,使粒子群可以快速收斂到最優(yōu)解或近似最優(yōu)解。大量的仿真結(jié)果表明蒙特卡洛增強(qiáng)粒子群優(yōu)化的信道選擇算法明顯優(yōu)于現(xiàn)有的相關(guān)算法,可以使無(wú)線(xiàn)監(jiān)測(cè)網(wǎng)絡(luò)達(dá)到更高的監(jiān)測(cè)質(zhì)量QOM,算法具有更低的計(jì)算復(fù)雜度和更快的收斂性速度。實(shí)際測(cè)試結(jié)果也證明了該算法的有效性。(3)針對(duì)無(wú)線(xiàn)監(jiān)測(cè)網(wǎng)絡(luò)數(shù)據(jù)匯聚過(guò)程中的多信道TDMA時(shí)隙調(diào)度問(wèn)題,提出了一種基于概率選擇的分布式頂點(diǎn)著色算法。首先基于無(wú)線(xiàn)監(jiān)測(cè)網(wǎng)絡(luò)拓?fù)錁?gòu)建路由樹(shù),形成干擾圖,從而將上述資源調(diào)度問(wèn)題轉(zhuǎn)化為干擾圖的頂點(diǎn)二重著色問(wèn)題,其目標(biāo)是最小化網(wǎng)絡(luò)通信沖突；然后根據(jù)目標(biāo)函數(shù),計(jì)算頂點(diǎn)選取顏色組合的概率,并按概率完成對(duì)信道和時(shí)隙的選擇。在不同網(wǎng)絡(luò)條件下的一系列對(duì)比仿真結(jié)果表明該算法可以有效減少網(wǎng)絡(luò)沖突數(shù),提高網(wǎng)絡(luò)吞吐量,減小網(wǎng)絡(luò)傳輸延時(shí)和調(diào)度長(zhǎng)度,從而使無(wú)線(xiàn)監(jiān)測(cè)網(wǎng)絡(luò)達(dá)到較高的數(shù)據(jù)匯聚性能。(4)設(shè)計(jì)了一種基于序列學(xué)習(xí)的網(wǎng)絡(luò)用戶(hù)信息感知策略。作為信道選擇算法應(yīng)用的前提條件,網(wǎng)絡(luò)的拓?fù)浣Y(jié)構(gòu)和用戶(hù)信息(工作信道、通信概率或權(quán)值)必須是已知的。本文給出了一種基于序列學(xué)習(xí)的用戶(hù)信息預(yù)測(cè)機(jī)制,有助于sniffer在全網(wǎng)信息收集操作的周期內(nèi)準(zhǔn)確掌握用戶(hù)的工作信道和通信概率或權(quán)值,從而為信道選擇算法提供重要依據(jù)。(5)設(shè)計(jì)了一種無(wú)線(xiàn)監(jiān)測(cè)網(wǎng)絡(luò)信道選擇算法仿真軟件。軟件支持用戶(hù)自定義網(wǎng)絡(luò)場(chǎng)景以及節(jié)點(diǎn)用戶(hù)二分圖,集成和編譯用戶(hù)算法,測(cè)試算法執(zhí)行效果,圖形顯示無(wú)線(xiàn)監(jiān)測(cè)網(wǎng)絡(luò)中監(jiān)測(cè)節(jié)點(diǎn)的信道選擇過(guò)程和結(jié)果,評(píng)價(jià)算法性能指標(biāo)。基于該仿真軟件,對(duì)該文所提出的算法和策略進(jìn)行了有效性測(cè)試,得到了一系列仿真數(shù)據(jù),進(jìn)一步驗(yàn)證了所提出方法的綜合有效性以及不足之處,并為下一步研究和相關(guān)科研工作奠定了基礎(chǔ)。本文研究無(wú)線(xiàn)監(jiān)測(cè)網(wǎng)絡(luò)優(yōu)化QOM的信道選擇和資源調(diào)度機(jī)制,提出了相應(yīng)的算法、策略和仿真平臺(tái),構(gòu)建了較為完善的理論方法體系,相關(guān)成果對(duì)無(wú)線(xiàn)監(jiān)測(cè)網(wǎng)絡(luò)技術(shù)的發(fā)展具有推動(dòng)作用和參考價(jià)值。
[Abstract]:With the expansion of network scale and rich applications, ensure the network performance, security and stability is facing increasing challenges. Using multiple wireless sniffer in wireless networks (sniffer) real-time collection of user data, can realize wireless network fault diagnosis and resource management, to enhance the performance of the network. To ensure network security, it is important to improve the user experience. Due to a limited number of sniffer, the configuration of hardware and software so how to optimize the scheduling of each sniffer, so that they cover the largest number of Internet users, access network data most, thereby maximizing the network quality monitoring (Quality of Monitoring, QoM) has become one of the hot topics today. This paper summarizes the current situation of the theory and technology of wireless monitoring network optimization QOM, channel allocation / focus on the optimization of sniffer method to select high QOM and The algorithm, and through theoretical derivation, the validity of the simulation and actual test results prove that the proposed method in this paper. The main research work and innovations are as follows: (1) summarizes the concepts and research status of wireless monitoring network. Summarizes the definition of wireless monitoring network, classification and system framework; discusses the method of wireless monitoring network optimization of QOM, introduced by sniffer / channel allocation optimization selection to improve various models and methods of QOM, and from a variety of performance evaluation of existing methods are analyzed and compared; the wireless monitoring network optimization QOM the key problems to be solved, and this research ideas and arrangements (2). For the problem of selecting sniffer channel wireless monitoring network data collection process, puts forward a method of Monte Carlo particle swarm optimization enhanced sniffer channel selection algorithm. Design a two-dimensional mapping Particle encoding and mobile solutions, and modify the solution into the Monte Carlo method, the particle swarm can quickly converge to the optimal solution or approximate optimal solution. The results of simulation show that the Monte Carlo enhanced particle swarm optimization algorithm related channel selection algorithm is obviously superior to the existing, can make the wireless monitoring network to monitor higher quality QOM that algorithm has lower complexity and faster convergence speed. The actual test results demonstrate the effectiveness of the algorithm. (3) the gap scheduling problem of multi channel TDMA wireless monitoring network data gathering process, this paper proposes a distributed vertex coloring algorithm based on probability based on the routing tree. The wireless monitoring network topology construction, the formation of an interference graph, thus the resource scheduling problem into the interference graph vertex coloring problem of double, the goal is to minimize network Communication conflict; then according to the objective function, selection probability calculation of vertex color combinations, and the completion of the channel and time slot selection according to the probability. A series of simulation results under different network conditions show that the proposed algorithm can effectively reduce the network conflict, improve the network throughput, reduce network transmission delay and scheduling length, so as to make the radio the monitoring network to achieve higher data convergence performance. (4) to design a strategy of network user's information perception based on sequence learning. As a prerequisite for the application of channel selection algorithm, topology and user information network (working channel, communication probability or weights) must be known. This paper presents a prediction mechanism of sequence learning based on user information, help sniffer in the cycle of the whole network of information collection in accurately grasp the user's work and communication channel probabilities or weights, so as to Channel selection algorithm provides an important basis. (5) the design of a wireless monitoring network channel selection algorithm. Simulation software software supports user-defined network scenarios and node users two figure, integrated and compiled user test algorithm, algorithm performance, graphical display of the process and results of channel wireless monitoring monitoring nodes in the network selection, evaluation algorithm performance. The simulation software based on the algorithm and the proposed strategy for the validity of the test, we obtained a series of simulation data, further verify the comprehensive effectiveness of the proposed method and shortcomings, and to lay a foundation for the next research and the related research work. This paper studies the wireless monitoring network optimization of QOM channel selection and resource scheduling mechanism, put forward the corresponding strategies and algorithms, simulation platform, constructs a theoretical system of relatively perfect method, relevant results of The development of wireless monitoring network technology has the role of promoting and referential value.

【學(xué)位授予單位】：合肥工業(yè)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類(lèi)號(hào)】：TN92;TP391.9

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