本文選題：網(wǎng)絡(luò)層析成像 + 性能管理　； 參考：《北京郵電大學(xué)》2014年碩士論文

【摘要】：隨著互聯(lián)網(wǎng)的迅速發(fā)展,人們對網(wǎng)絡(luò)服務(wù)的依賴程度不斷提高,對網(wǎng)絡(luò)的性能也提出了更高的要求。網(wǎng)絡(luò)性能測量是進(jìn)行網(wǎng)絡(luò)拓?fù)�、流量、行為建模分析的基礎(chǔ)和驗(yàn)證手段。如何用較低的代價(jià),準(zhǔn)確地測量得到整個(gè)網(wǎng)絡(luò)的運(yùn)行狀況是網(wǎng)絡(luò)測量研究中的主要內(nèi)容。在IP網(wǎng)傳遞信息的過程中,網(wǎng)絡(luò)端到端路徑丟包率和網(wǎng)絡(luò)鏈路丟包率能夠反映網(wǎng)絡(luò)的運(yùn)行狀況和擁塞程度,是網(wǎng)絡(luò)性能的重要指標(biāo)。因此如何快速準(zhǔn)確地得到路徑與鏈路丟包率成為眾多研究者研究的熱點(diǎn)。 本文首先提出了一種基于網(wǎng)絡(luò)層析成像的路徑丟包率推理方法,可通過測量r條分布均勻的獨(dú)立路徑較準(zhǔn)確地推理出剩余路徑的丟包率。新方法利用先前探測返回的結(jié)果自適應(yīng)的選擇下一個(gè)探測路徑,對非擁塞的路徑的刪減使得路由矩陣規(guī)模變小,從而大大降低了獨(dú)立路徑個(gè)數(shù)。并且該方法不需要求解鏈路丟包率的值即可得到所有剩余路徑丟包率的值,從而大大降低了算法復(fù)雜度。實(shí)驗(yàn)表明新方法在保證推理準(zhǔn)確度的條件下,篩選出的獨(dú)立路徑條數(shù)較已有經(jīng)典方法減少了5%-14%。 由于現(xiàn)有的網(wǎng)絡(luò)鏈路丟包率推理算法端到端探測比較困難、算法復(fù)雜度比較高,為了解決上述問題,本文還提出一種性能比較高的、新的鏈路丟包率推理算法。新算法首先建立代數(shù)模型,得到部分可確定鏈路的通過率,然后將可確定鏈路從方程中移除,之后將鏈路劃分為若干獨(dú)立子集,最后將每個(gè)子集的方程組求解問題轉(zhuǎn)化為非線性規(guī)劃的最優(yōu)化問題,從而在運(yùn)算時(shí)間盡量短、網(wǎng)絡(luò)探測盡量少的情況下推理求得比較準(zhǔn)確的數(shù)據(jù)。我們通過仿真實(shí)驗(yàn)與LIA算法以及LIABLI算法進(jìn)行了對比、和分析,盡管新算法僅用了2%的探測,但是診斷準(zhǔn)確度、推理準(zhǔn)確度以及運(yùn)行時(shí)間明顯得到改善。
[Abstract]:With the rapid development of the Internet, people rely on network services constantly, and put forward higher requirements for the performance of the network. Network performance measurement is the basis and verification method for modeling and analyzing network topology, traffic and behavior. How to accurately measure the operation of the whole network at lower cost is the main content of the network measurement research. In the process of transmitting information in IP network, the network end-to-end path packet loss rate and network link loss rate can reflect the network performance and congestion degree, which is an important index of network performance. Therefore, how to quickly and accurately obtain the path and link packet loss rate has become a hot topic for many researchers. In this paper, a path packet loss rate reasoning method based on network tomography is proposed, which can accurately infer the packet loss rate of the remaining path by measuring the independent path with uniform r distribution. The new method adaptively selects the next detection path using the results of the previous detection returns, and the deletion of the non-congested path makes the routing matrix smaller, thus greatly reducing the number of independent paths. Moreover, the method can get the value of all the remaining paths without solving the value of the link packet loss rate, which greatly reduces the complexity of the algorithm. Experiments show that the new method reduces the number of independent path bars by 5-14 compared with the classical method under the condition that the reasoning accuracy is guaranteed. Due to the difficulty of end-to-end detection and the high complexity of the existing network link packet loss rate reasoning algorithms, in order to solve the above problems, a new link packet loss rate reasoning algorithm with high performance is proposed in this paper. The new algorithm first establishes an algebraic model to obtain the pass rate of a partially determinable link, then removes the determinable link from the equation, then divides the link into several independent subsets. Finally, the problem of solving the equations of each subset is transformed into an optimization problem of nonlinear programming, so that the more accurate data can be obtained by reasoning under the condition that the computing time is as short as possible and the network detection is as little as possible. The simulation results are compared with LIA algorithm and LIABLI algorithm. Although the new algorithm uses only 2% detection, the diagnostic accuracy, reasoning accuracy and running time are improved obviously.
【學(xué)位授予單位】：北京郵電大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TP393.06

【參考文獻(xiàn)】

相關(guān)期刊論文 前9條

1 陳雷;董博;王雪;;基于SNMP協(xié)議的全局網(wǎng)絡(luò)流量分析系統(tǒng)的設(shè)計(jì)與實(shí)現(xiàn)[J];大連理工大學(xué)學(xué)報(bào);2005年S1期

2 張濤,陳鳴,謝希仁;基于目錄服務(wù)的企業(yè)網(wǎng)SNMP管理數(shù)據(jù)安全模型[J];東南大學(xué)學(xué)報(bào)(自然科學(xué)版);2000年06期

3 張志勇;胡光岷;;一種新的故障鏈路識別算法RPI[J];電子與信息學(xué)報(bào);2011年08期

4 顧然;邱雪松;喬焰;李娟;孟洛明;;基于非線性規(guī)劃的鏈路丟包率推理算法[J];電子與信息學(xué)報(bào);2012年06期

5 錢峰;胡光岷;;網(wǎng)絡(luò)層析成像研究綜述[J];計(jì)算機(jī)科學(xué);2006年09期

6 趙佐;蔡皖東;;基于先驗(yàn)概率的性能降級鏈路推斷方法[J];計(jì)算機(jī)工程;2010年03期

7 李天昀,葛臨東;綜述MATLAB與VC++的交互編程[J];計(jì)算機(jī)仿真;2004年09期

8 張宏莉,方濱興,胡銘曾,姜譽(yù),詹春艷,張樹峰;Internet測量與分析綜述[J];軟件學(xué)報(bào);2003年01期

9 趙洪華;陳鳴;;基于網(wǎng)絡(luò)層析成像技術(shù)的拓?fù)渫茢郲J];軟件學(xué)報(bào);2010年01期

，

本文編號：1795072