本文選題：Ad + Hoc　； 參考：《中國石油大學(xué)(華東)》2014年碩士論文

【摘要】：Ad Hoc網(wǎng)絡(luò)是一種臨時(shí)的多跳的能夠快速自動組網(wǎng)的通信網(wǎng)絡(luò)。在這種網(wǎng)絡(luò)中,所有的節(jié)點(diǎn)都是帶有無線收發(fā)器的移動終端,節(jié)點(diǎn)之間全部通過帶寬有限的無線鏈路進(jìn)行通信。它不需要固定基礎(chǔ)設(shè)施的支持,沒有固定的拓?fù)浣Y(jié)構(gòu),具有很強(qiáng)的魯棒性和抗毀性。因此,它被廣泛的應(yīng)用在軍事領(lǐng)域、自然災(zāi)害應(yīng)急處理、科學(xué)考察、探險(xiǎn)、交互式演講、共享信息的商業(yè)會議、緊急通信等等社會領(lǐng)域。因?yàn)楝F(xiàn)有的基于傳統(tǒng)固定網(wǎng)絡(luò)的路由協(xié)議無法在其中取得滿足實(shí)際需求的路由性能,所以研究能夠均衡網(wǎng)絡(luò)流量和節(jié)點(diǎn)的能量消耗的Ad Hoc網(wǎng)絡(luò)Qos多播路由算法就成為了Ad Hoc網(wǎng)絡(luò)技術(shù)研究的重要內(nèi)容。蟻群優(yōu)化算法(ACO)是由意大利學(xué)者M(jìn)arco Dorigo在1991年受到螞蟻覓食行為的啟發(fā)而提出的一種基于群體智能的啟發(fā)式搜索算法。蟻群算法具有很強(qiáng)的魯棒性、自適應(yīng)性、正反饋性和并行性,且不依賴于具體問題的數(shù)學(xué)描述,是一種解決NP-完全問題的有效方法。因?yàn)槲浵亴ぢ返男袨榕cAd Hoc網(wǎng)絡(luò)中數(shù)據(jù)分組的傳輸方式有著很多相似之處,所以蟻群算法為Ad Hoc網(wǎng)絡(luò)路由協(xié)議的設(shè)計(jì)就提供了一個(gè)重要的參考。本文基于AntNet算法和Ad Hoc網(wǎng)絡(luò)的特點(diǎn),提出了一種基于AntNet算法且能夠均衡網(wǎng)絡(luò)能量狀態(tài)的Ad Hoc網(wǎng)絡(luò)OoS多播路由算法-AEQMR。該算法通過使用路徑的能量狀態(tài)和其他QoS參數(shù)來更新信息素表,這就使得螞蟻的尋路行為均衡了網(wǎng)絡(luò)節(jié)點(diǎn)的能耗和網(wǎng)絡(luò)中數(shù)據(jù)的流向,并最終延長了整個(gè)網(wǎng)絡(luò)的生存時(shí)間。在螞蟻代理的數(shù)據(jù)結(jié)構(gòu)中,利用改進(jìn)的數(shù)據(jù)棧來記錄螞蟻代理在構(gòu)建路徑過程中形成的一段段子路徑的能量狀態(tài)和其他QoS參數(shù)情況。在節(jié)點(diǎn)上,利用改進(jìn)的網(wǎng)絡(luò)狀態(tài)統(tǒng)計(jì)模型和信息素更新規(guī)則并結(jié)合螞蟻代理所收集的網(wǎng)絡(luò)信息來更新節(jié)點(diǎn)信息素矩陣。數(shù)據(jù)包根據(jù)每個(gè)中間節(jié)點(diǎn)上的與當(dāng)前網(wǎng)絡(luò)狀態(tài)相關(guān)的信息矩陣來選擇下一個(gè)要到達(dá)的節(jié)點(diǎn)。因此,數(shù)據(jù)包在到達(dá)目的節(jié)點(diǎn)的過程中,每次選路都基于當(dāng)前最優(yōu)的路徑。在相同的場景下,通過OMNET++仿真軟件,本文對該算法和其他的Ad Hoc網(wǎng)絡(luò)路由協(xié)議分別進(jìn)行了仿真實(shí)驗(yàn),并分析比較了實(shí)驗(yàn)結(jié)果。仿真數(shù)據(jù)說明了該算法在縮短時(shí)延和均衡網(wǎng)絡(luò)能量狀態(tài)分布上具有優(yōu)良的性能。
[Abstract]:Ad Hoc network is a kind of temporary multi-hop communication network which can be quickly and automatically organized. In this network, all nodes are mobile terminals with wireless transceivers, and all nodes communicate via wireless links with limited bandwidth. It does not need the support of fixed infrastructure, has no fixed topology, and has strong robustness and survivability. Therefore, it is widely used in the military field, natural disaster emergency response, scientific exploration, interactive lectures, information sharing business meetings, emergency communications and other social fields. Because the existing routing protocols based on traditional fixed networks cannot achieve routing performance that meets the actual requirements, Therefore, the research of QoS multicast routing algorithm for Ad Hoc networks, which can balance network traffic and energy consumption of nodes, has become an important part of Ad Hoc network technology. Ant colony optimization (ACO) is a heuristic search algorithm based on swarm intelligence proposed by Italian scholar Marco Dorigo in 1991 inspired by ant foraging behavior. Ant colony algorithm has strong robustness, adaptability, positive feedback and parallelism, and does not depend on the mathematical description of specific problems. It is an effective method to solve NP-complete problems. Because the behavior of ant routing is similar to the transmission of data packets in Ad Hoc networks, ant colony algorithm provides an important reference for the design of routing protocols in Ad Hoc networks. Based on the characteristics of AntNet algorithm and Ad Hoc network, this paper presents an OoS multicast routing algorithm based on AntNet algorithm, which can balance the energy state of Ad Hoc network. The algorithm updates the pheromone table by using the energy state of the path and other QoS parameters, which makes the routing behavior of ants equalize the energy consumption of the network node and the flow of data in the network, and finally prolong the lifetime of the whole network. In the data structure of ant agent, the improved data stack is used to record the energy state and other QoS parameters of a segment of sub-path formed by ant agent in the course of constructing path. The node pheromone matrix is updated by using the improved network state statistics model and pheromone updating rules and the network information collected by ant agents. The packet selects the next node to be reached based on the information matrix on each intermediate node related to the current network state. Therefore, in the process of reaching the destination node, each routing is based on the current optimal path. In the same scenario, the algorithm and other Ad Hoc network routing protocols are simulated by OMNET simulation software, and the experimental results are analyzed and compared. The simulation results show that the algorithm has good performance in reducing delay and equalizing network energy state distribution.
【學(xué)位授予單位】：中國石油大學(xué)(華東)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TN929.5;TP18

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