內(nèi)容中心網(wǎng)絡(luò)中路由器關(guān)鍵模塊的研究
發(fā)布時(shí)間：2018-12-27 08:58
【摘要】：當(dāng)前不斷豐富的互聯(lián)網(wǎng)應(yīng)用給傳統(tǒng)的IP網(wǎng)絡(luò)帶來了諸多挑戰(zhàn),為了更好地滿足用戶高效、便捷地訪問網(wǎng)絡(luò)中內(nèi)容和服務(wù)的需求,以內(nèi)容為中心(Named Data Networking,NDN)的未來互聯(lián)網(wǎng)架構(gòu)應(yīng)運(yùn)而生。內(nèi)容中心網(wǎng)絡(luò)有三個(gè)非常重要的特點(diǎn):1)路由器可以緩存網(wǎng)絡(luò)中的大量內(nèi)容,用于服務(wù)后續(xù)的請(qǐng)求;2)根據(jù)內(nèi)容或者服務(wù)的名字進(jìn)行路由和轉(zhuǎn)發(fā);3)需要有狀態(tài)路由,即在轉(zhuǎn)發(fā)時(shí)維護(hù)與路由相關(guān)的狀態(tài)。這三個(gè)功能分別對(duì)應(yīng)數(shù)據(jù)平面上的三個(gè)關(guān)鍵模塊:內(nèi)容倉庫(Content Store,CS)、轉(zhuǎn)發(fā)表(Forwarding Information Base,FIB)以及請(qǐng)求暫存表(Pending Interest Table,PIT)。本文針對(duì)這三個(gè)模塊開展了研究,主要成果如下:1.內(nèi)容倉庫是內(nèi)容路由器的一項(xiàng)基本功能,該功能區(qū)別于傳統(tǒng)的包緩沖功能,因而需要完全不同的存儲(chǔ)架構(gòu)。本文提出了存儲(chǔ)卡(storage)的概念,并利用存儲(chǔ)卡搭建了分布式的存儲(chǔ)架構(gòu)來實(shí)現(xiàn)內(nèi)容倉庫,并且同時(shí)采用模型和仿真比較了該架構(gòu)下多種管理策略的性能差異。實(shí)驗(yàn)結(jié)果表明,“一致性哈希”管理策略能夠在該硬件框架下,以極小的額外開銷達(dá)到非常接近理想管理策略的性能。2.數(shù)據(jù)平面需要順序地查找CS、PIT和FIB以實(shí)現(xiàn)轉(zhuǎn)發(fā),CS和PIT要求精確匹配,而FIB要求最長前綴匹配;并且查找基于名字而不是IP地址,名字查找比IP地址查找具有更高的復(fù)雜度。這使得大規(guī)模的、涉及多張表的高速率、低時(shí)延轉(zhuǎn)發(fā)成為一項(xiàng)艱巨的任務(wù)。為此,我們提出了“統(tǒng)一索引”的概念,把三張表的索引整合在一起,只需一次查找就能得出結(jié)果,避免了原來的三次查找,降低了轉(zhuǎn)發(fā)時(shí)延并提高了查找速率。3.鑒于名字轉(zhuǎn)發(fā)表體積巨大,本文提出一種名為CONSERT的最優(yōu)壓縮算法,經(jīng)過壓縮后的最優(yōu)轉(zhuǎn)發(fā)表擁有的前綴數(shù)量最少,而且轉(zhuǎn)發(fā)的行為保持不變。本文利用歸納法證明了其最優(yōu)性。實(shí)驗(yàn)表明,CONSERT算法能夠有效減少名字轉(zhuǎn)發(fā)表中的前綴數(shù)量,進(jìn)而降低存儲(chǔ)開銷。4.在數(shù)據(jù)平面上,PIT除了記錄路由的狀態(tài),同時(shí)還具有請(qǐng)求聚合的功能,即將多個(gè)相同的請(qǐng)求聚合為一個(gè),以減少向網(wǎng)絡(luò)上游(從用戶到服務(wù)器方向)轉(zhuǎn)發(fā)的流量。為了探索PIT請(qǐng)求聚合的比例和PIT表項(xiàng)的數(shù)量這兩個(gè)指標(biāo),本文提出對(duì)PIT的一種全新的觀點(diǎn):PIT是一個(gè)基于TTL(Time To Live)的緩存�；谶@一新的認(rèn)識(shí),我們提出了PIT的分析模型,并給出了對(duì)上述兩個(gè)指標(biāo)的計(jì)算方法。模型和仿真的結(jié)果非常契合,表明了該模型的合理性和準(zhǔn)確性。
[Abstract]:The current abundant Internet applications bring many challenges to the traditional IP network. In order to better meet the needs of users for efficient and convenient access to the content and services in the network, content-centered (Named Data Networking, The future Internet architecture of NDN has emerged as the times require. Content-centric network has three very important features: 1) routers can cache a large amount of content in the network for service subsequent requests, 2) routing and forwarding according to the content or service name; 3) the need for stateful routing, that is, maintaining routing-related states when forwarding. These three functions correspond to three key modules in the data plane: content warehouse (Content Store,CS), forwarding table (Forwarding Information Base,FIB) and request staging table (Pending Interest Table,PIT). The main results are as follows: 1. Content warehouse is a basic function of content router, which is different from the traditional packet buffering function, so it needs a completely different storage architecture. In this paper, the concept of memory card (storage) is proposed, and a distributed storage architecture is built to implement the content warehouse. At the same time, the performance differences of various management strategies under this architecture are compared by using model and simulation. The experimental results show that the "consistent hash" management strategy can achieve the performance close to the ideal management strategy with minimal additional overhead under the hardware framework. 2. The data plane needs to find CS,PIT and FIB in order to forward, CS and PIT need to match accurately, while FIB requires the longest prefix matching, and the search is based on the name rather than the IP address, and the name lookup is more complex than IP address search. This makes large-scale, high-rate, low-delay forwarding of multiple tables a difficult task. For this reason, we put forward the concept of "unified index", integrating the indexes of three tables together, we can get the result only once, avoid the original three times lookup, reduce the delay of forwarding and improve the speed of searching. In view of the huge volume of the name forwarding table, this paper proposes an optimal compression algorithm called CONSERT. The compressed optimal forwarding table has the least number of prefixes and the behavior of forwarding remains unchanged. In this paper, we prove its optimality by inductive method. Experiments show that the CONSERT algorithm can effectively reduce the number of prefixes in the name forwarding table, and then reduce the storage overhead. 4. 4. In the data plane, the PIT not only records the state of the route, but also has the function of requesting aggregation, that is, many identical requests are aggregated into one to reduce the traffic of forwarding to the upstream of the network (from user to server). In order to explore the ratio of PIT request aggregation and the number of PIT table items, this paper presents a new view on PIT: PIT is a cache based on TTL (Time To Live). Based on this new understanding, we put forward the analysis model of PIT, and give the calculation method of the above two indexes. The results of the model and the simulation are in agreement with each other, which shows the rationality and accuracy of the model.
【學(xué)位授予單位】：清華大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2015
【分類號(hào)】：TP393.05
，
本文編號(hào)：2392818
[Abstract]:The current abundant Internet applications bring many challenges to the traditional IP network. In order to better meet the needs of users for efficient and convenient access to the content and services in the network, content-centered (Named Data Networking, The future Internet architecture of NDN has emerged as the times require. Content-centric network has three very important features: 1) routers can cache a large amount of content in the network for service subsequent requests, 2) routing and forwarding according to the content or service name; 3) the need for stateful routing, that is, maintaining routing-related states when forwarding. These three functions correspond to three key modules in the data plane: content warehouse (Content Store,CS), forwarding table (Forwarding Information Base,FIB) and request staging table (Pending Interest Table,PIT). The main results are as follows: 1. Content warehouse is a basic function of content router, which is different from the traditional packet buffering function, so it needs a completely different storage architecture. In this paper, the concept of memory card (storage) is proposed, and a distributed storage architecture is built to implement the content warehouse. At the same time, the performance differences of various management strategies under this architecture are compared by using model and simulation. The experimental results show that the "consistent hash" management strategy can achieve the performance close to the ideal management strategy with minimal additional overhead under the hardware framework. 2. The data plane needs to find CS,PIT and FIB in order to forward, CS and PIT need to match accurately, while FIB requires the longest prefix matching, and the search is based on the name rather than the IP address, and the name lookup is more complex than IP address search. This makes large-scale, high-rate, low-delay forwarding of multiple tables a difficult task. For this reason, we put forward the concept of "unified index", integrating the indexes of three tables together, we can get the result only once, avoid the original three times lookup, reduce the delay of forwarding and improve the speed of searching. In view of the huge volume of the name forwarding table, this paper proposes an optimal compression algorithm called CONSERT. The compressed optimal forwarding table has the least number of prefixes and the behavior of forwarding remains unchanged. In this paper, we prove its optimality by inductive method. Experiments show that the CONSERT algorithm can effectively reduce the number of prefixes in the name forwarding table, and then reduce the storage overhead. 4. 4. In the data plane, the PIT not only records the state of the route, but also has the function of requesting aggregation, that is, many identical requests are aggregated into one to reduce the traffic of forwarding to the upstream of the network (from user to server). In order to explore the ratio of PIT request aggregation and the number of PIT table items, this paper presents a new view on PIT: PIT is a cache based on TTL (Time To Live). Based on this new understanding, we put forward the analysis model of PIT, and give the calculation method of the above two indexes. The results of the model and the simulation are in agreement with each other, which shows the rationality and accuracy of the model.
【學(xué)位授予單位】：清華大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2015
【分類號(hào)】：TP393.05
，
本文編號(hào)：2392818
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