【摘要】：隨著網(wǎng)絡(luò)技術(shù)的更新和進(jìn)步，其應(yīng)用也變得多樣化。傳統(tǒng)Internet結(jié)構(gòu)在許多場景（如太空探測、戰(zhàn)場搜救、野生動(dòng)物研究等）中的應(yīng)用已暴露出不可彌補(bǔ)的弊端。 這類領(lǐng)域具有相同的基本特征：即網(wǎng)絡(luò)延遲大、鏈路拓?fù)渥兓l繁、傳輸速率不對稱、差錯(cuò)率高以及節(jié)點(diǎn)容量受限等。延遲容忍網(wǎng)絡(luò)（DTN）是為解決以上問題應(yīng)運(yùn)而生的一種新型網(wǎng)絡(luò)。為使DTN網(wǎng)絡(luò)能更有效地運(yùn)行于各類場景之下，對其路由算法的評估則顯得十分必要。 目前，有很多依據(jù)不同標(biāo)準(zhǔn)而進(jìn)行的DTN路由算法分類。以復(fù)制策略為共同基礎(chǔ)的分類中，包含了眾多的路由算法。其中，比較有代表性的有：Epdemic算法、Spray AndWait算法，它們都基于洪泛思想；PROPHET算法基于概率，MAXPRO算法基于調(diào)度。它們都是理論上較為成熟的算法。 本文針對5種常見的復(fù)制策略DTN路由算法，采用機(jī)會(huì)網(wǎng)絡(luò)模擬器ONE環(huán)境，進(jìn)行系列實(shí)驗(yàn)對算法性能進(jìn)行評估。與眾不同的是，本文采用了ONE的開放模型ExternalMovement，以真實(shí)車輛運(yùn)行軌跡數(shù)據(jù)為基礎(chǔ)進(jìn)行“模擬化”的真實(shí)場景重現(xiàn)，通過變換4類參數(shù)共進(jìn)行155次具體實(shí)驗(yàn)。兩組原始數(shù)據(jù)均來源于客觀世界：一組是舊金山500余輛出租車運(yùn)行軌跡數(shù)據(jù)；一組是國內(nèi)南方某市的7000余輛出租車運(yùn)行軌跡數(shù)據(jù)。由于出租車輛大多為小型車輛，活動(dòng)方式與運(yùn)行軌跡與普通車輛（路線固定的車輛如公交車、有軌電車等除外）并無太大差別，完全可以代表一般車輛運(yùn)行規(guī)律。這種基于真實(shí)數(shù)據(jù)的采樣模擬實(shí)驗(yàn)以及進(jìn)行算法評估，很大程度上消除了軟件模擬運(yùn)動(dòng)模型構(gòu)造DTN網(wǎng)絡(luò)的局限性，，更為客觀精確地體現(xiàn)了路由算法在應(yīng)用中的特性特征。 最后，基于投遞成功率、平均延遲時(shí)間、資源開銷比三個(gè)評估指標(biāo)對5種算法進(jìn)行了橫向和縱向比較，得出了一般性結(jié)論。
[Abstract]:With the update and progress of network technology, its application has become diversified. The application of traditional Internet structure in many scenarios (such as space exploration, battlefield search and rescue, wildlife research, etc.) has exposed irreparable drawbacks. This kind of domain has the same basic characteristics: the network delay is large, the link topology changes frequently, the transmission rate is asymmetric, the error rate is high, and the node capacity is limited. Delay tolerance network (DTN) is a new network to solve the above problems. In order to make DTN network run more effectively under various scenarios, it is necessary to evaluate its routing algorithm. At present, there are many DTN routing algorithms classified according to different standards. Many routing algorithms are included in the classification based on replication strategy. Among them, the representative ones are: Epdemic algorithm, Spray AndWait algorithm, they are based on flood idea, PROPHET algorithm is based on probability, MAXPRO algorithm is based on scheduling. They are mature algorithms in theory. In this paper, a series of experiments are carried out to evaluate the performance of five common replication strategy DTN routing algorithms using the ONE environment of the opportunistic network simulator. What is different is that ONE's open model ExternalMovement, is used to reproduce the real scene based on the real vehicle track data, and 155 concrete experiments are carried out by transforming four kinds of parameters. The two groups of original data are from the objective world: one is the track data of more than 500 taxis in San Francisco; the other is the track data of more than 7000 taxis in a city in the south of China. Because most of the rental vehicles are small vehicles, there is no great difference between the moving mode and the running track of the ordinary vehicles (except the vehicles with fixed routes, such as buses, trams, etc.), so it can fully represent the running rules of the general vehicles. The sampling simulation experiment based on real data and the evaluation of algorithm to a great extent eliminate the limitation of software simulation motion model to construct DTN network and more objectively and accurately reflect the characteristics of routing algorithm in application. Finally, based on the delivery success rate, average delay time and resource overhead ratio, five algorithms are compared horizontally and longitudinally, and a general conclusion is drawn.
【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TP393.02

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