本文選題：擁塞控制 + RED�。� 參考：《吉林大學(xué)》2014年碩士論文

【摘要】：當(dāng)今，互聯(lián)網(wǎng)發(fā)展中遇到的主要問(wèn)題之一，是網(wǎng)絡(luò)擁塞所導(dǎo)致的資源缺乏和流量分配不均，而擁塞問(wèn)題還會(huì)造成網(wǎng)絡(luò)數(shù)據(jù)傳輸?shù)难舆t，進(jìn)而加劇網(wǎng)絡(luò)擁塞的程度，更嚴(yán)重的情況下將會(huì)導(dǎo)致網(wǎng)絡(luò)崩潰，上述現(xiàn)象引起了研究者對(duì)網(wǎng)絡(luò)擁塞控制的高度重視。目前，網(wǎng)絡(luò)擁塞問(wèn)題仍然是不可避免的，如果僅僅依靠源端的擁塞控制機(jī)制，那么會(huì)大大降低網(wǎng)絡(luò)資源的利用率。解決這一問(wèn)題最有效的辦法就是隊(duì)列管理算法，隊(duì)列管理算法又分為主動(dòng)隊(duì)列管理算法和被動(dòng)隊(duì)列管理算法。目前廣泛使用的是主動(dòng)隊(duì)列管理算法，它通過(guò)將路由器中的隊(duì)列長(zhǎng)度控制在一個(gè)適當(dāng)值附近，從而能有效地減少數(shù)據(jù)包的延時(shí)，并且能夠提高鏈路利用率。因此，對(duì)主動(dòng)隊(duì)列管理算法的研究具有非常重要的意義。 隨著互聯(lián)網(wǎng)的飛速發(fā)展，現(xiàn)有的TCP擁塞控制機(jī)制在很多方面已經(jīng)無(wú)法滿(mǎn)足人們的需要，于是人們將擁塞控制研究擴(kuò)大到網(wǎng)絡(luò)的中間環(huán)節(jié)，出現(xiàn)了許多基于路由器的擁塞控制策略。隨機(jī)早期檢測(cè)算法RED(Random Early Detection)是網(wǎng)絡(luò)工程任務(wù)組IETF(Internet Engineering Task Force)推薦的基于路由器的擁塞控制算法。 本文的主要工作如下： 首先，本文詳細(xì)介紹了RED算法的參數(shù)設(shè)置，對(duì)TCP最大窗口問(wèn)題進(jìn)行了分析，并從Misra的隨機(jī)微分方程模型理論出發(fā)，利用數(shù)學(xué)手段對(duì)此模型進(jìn)行了一系列的處理，最后得到了一種新的估計(jì)隨機(jī)早期檢測(cè)算法參數(shù)——最大丟棄概率的方法。 其次，詳細(xì)介紹了RED算法中重新設(shè)置最大丟棄概率的方法：對(duì)于一個(gè)已經(jīng)確定的網(wǎng)絡(luò)，在設(shè)置參數(shù)時(shí)，，最大閾值通常設(shè)為最小閾值的2~3倍，期望的隊(duì)列長(zhǎng)度的大小可以根據(jù)實(shí)際需要設(shè)定。如果突發(fā)比較強(qiáng)或者對(duì)延時(shí)比較保守，就將隊(duì)列長(zhǎng)度設(shè)得稍小些；如果對(duì)丟包比較保守則將隊(duì)列長(zhǎng)度設(shè)得偏大些。這樣，本文提出的最大丟棄概率估計(jì)方法其實(shí)只與最小閾值和隊(duì)列長(zhǎng)度有關(guān)，當(dāng)這兩個(gè)參數(shù)確定以后，由推導(dǎo)出的公式即可計(jì)算出最大丟棄概率值。 最后，通過(guò)NS-2(Network Simulation Version2)仿真實(shí)驗(yàn)，利用重新設(shè)置的最大丟棄概率值對(duì)RED路由與DropTail路由的吞吐率和延時(shí)進(jìn)行了比較，并按照相同最大窗口限制和不同最大窗口限制兩種條件，對(duì)兩種算法下的瞬時(shí)隊(duì)列長(zhǎng)度、平均隊(duì)列長(zhǎng)度及丟包率進(jìn)行了比較與分析。最終驗(yàn)證了在重新設(shè)置最大丟棄概率后，RED算法瞬時(shí)隊(duì)長(zhǎng)、平均隊(duì)長(zhǎng)、丟包率、源端連接數(shù)等技術(shù)指標(biāo)均得到優(yōu)化，從而達(dá)到了降低網(wǎng)絡(luò)擁塞，提高傳輸質(zhì)量的目的。
[Abstract]:Nowadays, one of the main problems encountered in the development of the Internet is the lack of resources and the uneven distribution of traffic caused by network congestion, and the congestion problem will also lead to the delay of network data transmission, which will aggravate the degree of network congestion. More serious cases will lead to network collapse, which causes researchers to attach great importance to network congestion control. At present, the network congestion problem is still inevitable. If we only rely on the source congestion control mechanism, it will greatly reduce the utilization of network resources. The most effective way to solve this problem is queue management algorithm, which is divided into active queue management algorithm and passive queue management algorithm. At present, active queue management algorithm is widely used. It can effectively reduce the delay of data packets and improve the link utilization by controlling the queue length in routers near a suitable value. Therefore, the study of active queue management algorithms is of great significance. With the rapid development of the Internet, the existing TCP congestion control mechanism has been unable to meet the needs of people in many aspects, so the study of congestion control has been expanded to the intermediate link of the network. There are many router-based congestion control strategies. Random early Detection (RED(Random Early Detection) is a router-based congestion control algorithm recommended by IETF(Internet Engineering Task Force. The main work of this paper is as follows: First of all, the parameter setting of RED algorithm is introduced in detail, and the TCP maximum window problem is analyzed. Based on the stochastic differential equation model theory of Misra, a series of mathematical methods are used to deal with the model. Finally, a new method to estimate the parameter of the random early detection algorithm, the maximum drop probability, is obtained. Secondly, the method of resetting the maximum drop probability in the RED algorithm is introduced in detail: for a network that has been determined, the maximum threshold is usually set to 2 or 3 times the minimum threshold when the parameters are set. The size of the desired queue length can be set according to actual needs. If the burst is stronger or the delay is conservative, the queue length is set slightly smaller, and if the packet loss is more conservative, the queue length is larger. In this way, the maximum drop probability estimation method proposed in this paper is only related to the minimum threshold and queue length. When these two parameters are determined, the maximum drop probability can be calculated from the derived formula. Finally, through the NS-2(Network Simulation version 2) simulation experiment, the throughput and delay of RED routing and DropTail routing are compared by using the reset maximum drop probability value, and according to the same maximum window limit and different maximum window limitation conditions, The instantaneous queue length, average queue length and packet loss rate of the two algorithms are compared and analyzed. Finally, it is verified that the instantaneous length, average queue length, packet loss rate and the number of connections at the source end of the red algorithm are optimized after the maximum drop probability is set, so that the network congestion can be reduced and the transmission quality can be improved.
【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TP393.06

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本文編號(hào)：1801904