本文選題：分布式緩存 + 分布式傳輸�。� 參考：《西安電子科技大學》2014年碩士論文

【摘要】：本文提供了一種新的內(nèi)容分發(fā)網(wǎng)絡的架構(gòu)，即通過在網(wǎng)絡中部署具有低成本、大容量的緩存節(jié)點來減輕用戶下載文件對網(wǎng)絡回傳容量的造成的開銷，但也引入了內(nèi)容文件的緩存、傳輸?shù)葐栴}，加劇了系統(tǒng)的復雜度。因此對內(nèi)容分發(fā)過程的高效管理在內(nèi)容分發(fā)網(wǎng)絡中變的迫切且重要。 本文首先分析了內(nèi)容分發(fā)網(wǎng)絡中的分布式緩存問題和分布式傳輸調(diào)度問題，并且給出了針對這兩種問題的常見算法。然后研究了網(wǎng)絡編碼在基于分布式緩存的內(nèi)容分發(fā)網(wǎng)絡中的應用。即通過使用網(wǎng)絡編碼可以將文件的緩存問題和傳輸問題轉(zhuǎn)化成使網(wǎng)絡為每個移動用戶保證一個相對固定且足夠大的流速率的問題，從而為內(nèi)容文件的分發(fā)問題建立了一個流調(diào)度的模型。利用原始-對偶的分解方法對流調(diào)度問題進行分解可以得到中心服務器與helper節(jié)點之間的緩存分配問題和helper節(jié)點與移動用戶之間的帶寬分配問題。通過將原問題進行分解，每一個網(wǎng)絡節(jié)點可以獲得一個可以分布式運行的子算法，各個子算法之間聯(lián)合迭代，最終得出最優(yōu)的緩存、帶寬分配。 最后，考慮到移動無線環(huán)境動態(tài)變化的馬爾科夫特性，本文中將整個網(wǎng)絡拓撲的變化看為一個有限狀態(tài)的馬爾科夫鏈，，每一種網(wǎng)絡拓撲都是這個馬爾科夫鏈的一個平穩(wěn)分布。根據(jù)馬爾科夫狀態(tài)的平衡方程可以得到網(wǎng)絡拓撲的狀態(tài)轉(zhuǎn)移概率和轉(zhuǎn)移周期。運行分布式算法的節(jié)點可以根據(jù)這個狀態(tài)轉(zhuǎn)移概率和周期來進行自我配置從而使整個網(wǎng)絡的性能達到全局最優(yōu)。
[Abstract]:In this paper, a new architecture of content distribution network is proposed, in which the cost of downloading files to the network is reduced by deploying a low-cost, large-capacity cache node in the network. However, some problems such as cache and transmission of content files are introduced, which aggravate the complexity of the system. Therefore, the efficient management of the content distribution process becomes urgent and important in the content distribution network. In this paper, we first analyze the distributed cache problem and distributed transport scheduling problem in content distribution networks, and give some common algorithms for these two problems. Then the application of network coding in distributed cache-based content distribution network is studied. That is, by using network coding, the problem of file caching and transmission can be transformed into the problem of making the network guarantee a relatively fixed and sufficiently large flow rate for each mobile user. Thus, a flow scheduling model is established for the distribution of content files. The problem of cache allocation between the central server and the helper node and the bandwidth allocation problem between the helper node and the mobile user can be obtained by decomposing the primal-dual decomposition method for the convection scheduling problem. By decomposing the original problem, each network node can obtain a distributed sub-algorithm that can be run, each sub-algorithm iterates together, and finally the optimal cache and bandwidth allocation are obtained. Finally, considering the Markov characteristic of the dynamic change of mobile wireless environment, the change of the whole network topology is regarded as a finite state Markov chain in this paper, and each network topology is a stationary distribution of the Markov chain. According to the equilibrium equation of Markov state, the state transition probability and transition period of network topology can be obtained. The nodes running the distributed algorithm can self-configure according to the transition probability and period of the state so that the performance of the whole network can be optimized globally.
【學位授予單位】：西安電子科技大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TP393.02

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