Scalable High-Speed Route Search Mechanisms for IP Networks

過去幾年來World Wide Web的快速成長與網路上多媒體應用程式的劇增，都是大家所共見的。也因此網路上的流量每三個月就成長一倍；而區域網路(Local Area Networks, LAN)的設備與頻寬，也由原本的每秒10百萬位元 (megabit per second, Mbps) 增加至100Mbps，甚至每秒10億位元 (gigabit per second, Gbps)；所以我們便需要能夠負載每秒百萬(million)或10百萬封包(million packet per second, million pps)以上的高速路由器(router)，才能符合未來的需求。而對下一代的高速IP routers而言，IP位址找尋(IP lookup)的機制就是其中最關鍵的議題。由於IP routing需要對每個進入的packet，依其目的位址進行最長符合前置位元的尋找(longest prefix matching)，以求出對應下一站路由器(next hop router)位址之輸出埠(output port)。目前此過程因為較複雜，所以大多以軟體來實作，使得IP lookups成為router效能上最主要的瓶頸(bottleneck)。 在此論文中，我們提出一個高速的IP lookup機制來找尋最佳前置位元(Best Matching Prefix, BMP)，所使用的轉送表(forwarding tables)中包含前置位元資訊表(Prefix Information Tables, PITs)與位址找尋表(Lookup Table, LT)，用來提供快速找尋的指引。此方法在位址長度或路由表增加時，仍可保持極佳的擴充性。在IPv4下，最少需要1次記憶體存取(memory access)而最多只需1次雜湊(hash)程序加2次的記憶體存取即可完成IP lookups的過程，找到其BMP。此外，我們以此基本方法加以改進，則所需的BMP找尋時間可減少至最少1次而最多只需2次的記憶體存取。而以IPv4骨幹網路路由器(backbone router)上的45,000 routing entries之資料做測試，則此架構只需約560 KBytes；即使為了加速IP lookup而使用改良之方法，其記憶體的需求仍不超過930 KBytes。以50ns的動態存取記憶體(DRAM)來做評估，其IP lookups的速度可達10’106 packet per second(pps)；若以5ns的同步動態存取記憶體(SDRAM)來做評估，則IP lookups的速度可達100’106 pps。因此當未來記憶體的速度越快時，IP lookups的速度也會隨之成線性增進。此外，我們所提出之架構並不需要複雜的壓縮技術來減少對記憶體的需求，其操作步驟非常簡單，可容易的提供硬體之實作，因此對下一代的IP routers而言是非常好的選擇。The past few years have witnessed the advent of the World Wide Web and the emergence of multimedia applications over the Internet. With the amount of the traffic doubling every three months and the introduction of the LAN equipments of ever increasing speeds from 100Mbps to Gbps, high-speed routers that process millions or 10's of millions of packets per second are needed to meet the future demands. One of the key design issues for the next generation IP routers is the IP lookup mechanism. For each incoming IP packet, the IP routing requires to perform a longest prefix matching on the address lookup in order to determine the packet's next hop. Currently, the process is done in software and has become one of the major bottlenecks of the router peformance. In this thesis, we propose two high-speed IP lookup schemes for the Best Matching Prefix (BMP) by using forwarding tables consisting of Prefix Information Tables (PITs) and Lookup Tables (LTs) that provide guidelines for efficient searches. The schemes scale very well as the size of the address and the routing table increase. For IP lookup in IPv4, the basic scheme needs 1 memory access in the best case, and 2 memory accesses plus one hash in the worst case to locate the BMP. The lookup speed is independent of the size of the routing table. It requires only 560 KBytes of memory space when about 45,000 routing table entries in the backbone are logged for simulation. When 50ns DRAM is used for the forwarding tables, the scheme offers lookup speed of 10 millions packets per second (10 MPPS). The lookup speed of the basic scheme can further be improved to be 1 memory access in the best case and 2 memory accesses in the worst case with about 930 KBytes of memory used for the same number of routing table entries. The lookup speed can be improved linearly with the speedup of the memory used. Further, it does not need complex compression mechanisms to reduce the memory requirement. Its operation is simple, lending itself for easy hardware implementation and therefore is a good candidate to be used in the next generation IP routers.論文摘要2 ABSTRACT3 第一章簡介8 第二章 相關研究11 2.1 TRIES11 2.2 SCALABLE HIGH SPEED IP ROUTING LOOKUPS11 2.3 IP LOOKUPS USING MULTIWAY AND MULTICOLUMN SEARCH12 2.4 SMALL FORWARDING TABLES FOR FAST ROUTING LOOKUPS13 2.5 IP-ADDRESS LOOKUP USING LC-TRIES15 2.6 FAST ADDRESS LOOKUPS USING CONTROLLED PREFIX EXPANSION16 2.7 A FAST IP ROUTING LOOKUP SCHEME FOR GIGABIT SWITCH ROUTER18 2.8 ON FAST ADDRESS LOOKUP ALGORITHMS19 2.9 ROUTING LOOKUPS IN HARDWARE AT MEMORY ACCESS SPEEDS20 2.10 結語21 第三章 基本架構22 3.1 名詞定義與資料結構之使用23 3.2 IP路徑找尋之機制27 3.3 實例說明29 3.4 基本架構之改進方法32 第四章 基本架構之改良34 4.1 名詞定義與資料結構之使用34 4.2 IP路徑找尋之機制35 4.3 結語35 第五章 FORWARDING TABLES之更新36 5.1 "HOLE" PROBLEMS37 5.2 新增之運作39 5.3 刪除之運作40 5.4 更新之運作43 5.5 結語44 第六章 效能評估45 6.1 FORWARDING TABLES之記憶體需求的評估45 6.2 路徑找尋之效能評估47 6.3 更新之效能評估48 6.4 比較與分析49 第七章 結論與未來展望52 參考文獻53 中英文名詞對照表5