A parallel IP-address forwarding approach based on partitioned lookup table techniques

Continuing growth in traffic, the size of routing table as well as the link speeds puts great challenge on the performance of Internet address lookup. The packet forwarding engine need perform 150 million IP address lookups per second for a 100Gbps line card while accommodating up to 500,000 prefixes and very likely 1M in the near future. TCAM based lookup solutions do not scale well for the next-generation due to its high power dissipation and large footprint. Algorithmic solutions can achieve high throughputs with hardware parallelism and compact storage needs, but can hardly scale simultaneously in the three dimensions of increased table size, throughput, and prefix length as IP moves to 64 bit IPv6 addresses. We propose a novel IPv6 lookup algorithm called Prefix Range Based Binary Search (PRB-BS) using binary search over hash tables organized by the range of prefix length. By eliminating the path information of the subtrie our scheme reduces the memory demands considerably. Besides, the binary search scheme based on prefix range reduces the worst case time of hash lookups to log2L, with L being the number of subtrie layers. We also introduce asymmetry binary search to further reduce memory demands and memory accesses. Compared with the tree bitmap algorithm widely used by many modern routers the memory requirements of PRB-BS algorithm is about 55% of the tree bitmap algorithm. The experiment results also show that the average search depth of PRB-BS algorithm is stable at 2 with the increased number of prefixes, which reflects better scalability of PRB-BS algorithm.

The searching denotes a process that aims to find a specific item in the data set. After performing the process of searching, the desired items are likely found or not. This kind of investigations was actually demonstrated by some researchers. For each search algorithm, the previous studies just focused to obtain the search time but did not obtain the number of passed-nodes. Furthermore, the results obtained with regards to the search time were not reported systematically. Hence, this study investigates how fast the desired items were found and how few passed-nodes were obtained when searching desired items by using three search algorithms. These algorithms were linear, binary, and interpolation algorithms. By using search algorithms, one hundred twenty desired items were searched in a collection of active-student data (3946 records in total). The search time needed to find a specific item and the number of passed nodes were recorded. The results showed that the searching process with linear search algorithm required more time and more passed-nodes than binary and interpolation search algorithms. Following this, searching time and the number of passed-nodes for desired items were significantly smaller for binary search than for the interpolation search algorithm. Taken together, the present results suggested that the binary search could be considered as a solid algorithm in searching a specific item in the data set utilized by the current study.

The size of router forwarding tables is a critical aspect of the quality of a network design. Oversized forwarding tables not only force enterprises to purchase expensive hardware, which is a significant operational cost, but also make issues such as power consumption and heat generation more prominent. The size of forwarding tables is a direct result of the IP prefix assignment scheme. Unfortunately, today the prefix assignment is done entirely by hand in an ad-hoc fashion, which often produces unnecessarily large forwarding tables. This paper presents a systematic, algorithmic, and fully-automated approach to prefix assignment, which is capable of producing compact forwarding tables by facilitating prefix-based aggregation. In doing so, we first introduce a mathematical formulation for the prefix assignment problem, and then present the design of a novel and efficient algorithmic solution. Our solution maps the prefix assignment problem to standard graph operations by exploiting the inherent structure in IP addresses, and leverages techniques from graph theory to solve the problem. The solution has been implemented in a software prototype which works in a fully automated way. Evaluation using real-world configuration snapshots from four operational networks is presented, and the results demonstrate the effectiveness and efficiency of our approach.

An efficient IP address lookup algorithm based on a small balanced tree using entry reduction

One unique architectural benefit of Named Data Networking (NDN) is adaptive forwarding, i.e., the forwarding plane is able to observe data retrieval performance of past Interests and use it to adjust forwarding decisions for future Interests. To be effective, adaptive forwarding assumes Interest Routing Locality, meaning that Interests sharing the same prefix are likely to follow a similar forwarding path within a short period of time. Therefore, past observations can provide insight into how forwarding will likely perform for the same prefix in the near future. Since Interests can have multiple common prefixes with different lengths, the real challenge is determining which prefix length should be used in adaptive forwarding to record path measurements - we refer to this as the Prefix Granularity Problem. The longer the common prefix is, the better Interest Routing Locality. However, finer grained-prefixes cover fewer Interests each and require a larger forwarding table. Existing adaptive forwarding designs use a static prefix length, which is known to encounter issues in the event of partial network failures. In this work, we propose to dynamically aggregate and de-aggregate name prefixes in the forwarding table in order to use the prefixes that are the most appropriate given current network situation. In addition, to reduce the overhead of adaptive forwarding, we propose mechanisms to minimize the use of longest prefix matching during the processing of Data packets. Simulations demonstrate that the proposed techniques can result in better forwarding decisions in the event of partial network failures with significantly reduced overhead.

The IP address lookup in the communication link technologies is becoming a major bottleneck by exploring the exact matching and the parallel hashing in each prefix length. In this paper, we present an algorithm for IP address lookup and collision resolution to reduce memory space and solve collision for high speed routing based on multiple table indexing structure. Our scheme makes possible direct access in a designated IP prefix without replicating the forwarding table entries, and provides efficient collision resolution for fast route lookup with only small memory. Simulation results indicate that our algorithm provides a faster lookup than the conventional lookup schemes.

Multiway range trees: scalable IP lookup with fast updates

Search is considered to be an important functionality in a computational system. Search techniques are applied in file retrievals and indexing. Though there exists various search techniques, binary search is widely used in many applications due to its advantage over other search techniques namely linear and hash search. Binary search is easy to implement and is used to search for an element in a large search space. The worst case time complexity of binary search is O (log 2 n) where n is the number of elements (search space) in the array. However, in binary search, searching is performed on the entire search space. The complexity of binary search may be further reduced if the search space is reduced. This paper proposes an Ant Colony Optimization based Binary Search (ACOBS) algorithm to find an optimal search space for binary search. ACOBS algorithm categorizes the search space and the key element is searched only in a specific category where the key element can exist thereby reducing the search space. The time complexity of ACOBS algorithm is O (log 2 c) where c is the number of elements in the reduced search space and c < n. The proposal is best suited for real time applications where searching is performed on a large domain.KeywordsAnt colony optimizationBinary searchOptimal search space

Dalam ilmu komputer terdapat bermacam – macam algoritma untuk metoda pencarian (searching). Beberapa metoda pencarian yang pernah dipelajari adalah metoda pencarian linier (Linear / Sequential Search), pencarian biner (Binary Search) dan pencarian interpolasi (Interpolation Search). Masing – masing algoritma memiliki prasyarat dan cara serta waktu pelaksanaan yang berbeda. Pemilihan atas metoda pencarian dilakukan berdasarkan keadaan dan keinginan pengguna metoda yang biasanya tergantung pada jumlah data, jenis data dan struktur data yang digunakan. Pencarian (searching) merupakan suatu pekerjaan yang sering dikerjakan dalam kehidupan sehari – hari. Ada kalanya kita mencari sesuatu dengan tujuan hanya untuk mengetahui apakah data tersebut ada dalam sekumpulan data atau tidak, sementara di lain waktu mungkin kita menginginkan posisi dari data yang dicari tersebut. Pada tahap simulasi dan analisa, terdapat prosedur ‘SimulasiCari’, yang berfungsi untuk mensimulasikan tahapan – tahapan pencarian dan menampilkan hasil analisis dan prosedur kerja program dalam bentuk report. Prosedur ‘SimulasiCari’ terdiri atas 3 prosedur utama, yaitu ‘LinearSearch’, ‘BinarySearch’ dan ‘InterpolationSearch’. Prosedur ‘LinearSearch’ berfungsi untuk mensimulasikan tahapan pencarian dengan algoritma pencarian linier dan menampilkan hasil analisis dan prosedur kerja program dalam bentuk report. Prosedur ‘BinarySearch’ berfungsi untuk mensimulasikan tahapan pencarian dengan algoritma pencarian biner dan menampilkan hasil analisis dan prosedur kerja program dalam bentuk report. Prosedur ‘InterpolationSearch’ berfungsi untuk mensimulasikan tahapan pencarian dengan algoritma pencarian interpolasi dan menampilkan hasil analisis dan prosedur kerja program dalam bentuk report. Kata Kunci : Pencarian Linier (Linear / Sequential Search), Pencarian Biner (Binary Search) Dan Pencarian Interpolasi (Interpolation Search)

Architecture overview of cell switch router (CSR), that is one of actual implementation using label switching paradigm, and the CSR prototype system supporting standard ATM interfaces are described. CSR can operate both with PVC (permanent virtual connection) and with SVC (switched virtual connection) as the VC for cut-through packet forwarding. CSR contains cell switch fabric and IP packet switch fabric to achieve high throughput IP forwarding. IP packets are forwarded either through a cut-through packet transmission, in which packet are forwarded without reassembling IP packet nor IP header processing, or through a conventional hop-by-hop IP packet forwarding. This paper describes and proposes the mechanism to forward the connectionless IP packet flows at the CSR. A CSR prototype system has developed. The CSR prototype system uses PVC and SVC connections to transfer the IP packets. With the CSR prototype system, we can make sure that CSR system could establish the cut-through packet transmission path between the adjacent node with acceptable establishment delay, that was less than few hundred second. The SVC connections for cut- through packet transmission are established on demand using ATM Forum UNI 3.0 or UNI 3.1.

Given n records stored alphabetically on a tape, any comparison search procedure can be characterized by a binary tree. The complete binary tree (binary search) uses the minimum number of comparisons but not the minimum number of movements. The linear binary tree (sequential search) uses the minimum number of movements but not the minimum number of comparisons. A tape-optimal tree is a tree which minimizes the total cost of comparisons and movements. The tape-optimal tree is a “hybrid” of the linear tree and the complete binary tree, and is characterized for arbitrary n.

With the growth of Internet traffic and using Gb/s or 10 Gb/s links in backbone, the speed of forwarding packets in intermediate devices is crucial. Routers must be able to forward millions of packets per second on each of their interfaces. Finding a method that can speed up the IP lookup is one of the challenges in network research. There are two approaches to implement IP lookup, hardware-based and software-based. For software-based approach many algorithms have been proposed based on the tries concept. Some parallel algorithms have been suggested to exploit routers equipped with multi-core CPUs. In this paper, we propose a new approach that was constructed by combining the useful characteristics of the Priority trie and parallel processing. Our method consists of a trie and several subtries based on prefix length. These subtries processed by a specific thread to speed up IP lookup functionality. This proposed data structure inherits simplicity of Priority tries. Simulation results illustrate that our method speeds up IP lookup processing although memory usage has not been increased.

Computer networks have continued to make substantial advances in the past couple of decades through better technologies and methodologies employed. As the usage of the networks continues to increase exponentially, high throughput of the networks has to be maintained with various performance-efficient network algorithms. IP address lookup is one of the processes, the performance of which dearly affects the overall network performance. Hashing has been widely used for fast IP address lookup due to its simplicity, but mostly assuming on hashing from an address set with uniformly distributed key values. Performance from these known hashing techniques is far from optimal due to the high nonuniformity in actual IP address distribution. In this paper, we propose a preprocessing method for the IP address databases to extract certain regularity to allow for design of more efficient hashing algorithms based on XOR operations. Simulation results show an improvement in performance ranging from 35% to 72% on randomly generated addresses and several sample IP address databases. The paper also shows that the proposed algorithms deliver comparable performance to other well-known hashing algorithms such as the CRC and RS hashing while requiring much less hardware to implement and a much shorter time to perform.

IP forwarding technique in open flow switch can be done by comparing the destination IP address, which is stored in forwarding table with the input IP prefix. Ternary content-addressable memory (TCAM) is one of the popular mechanisms to store and forward IP packet where flow entries are organized in sorted manner. Searching a prefix value in TCAM uses longest prefix match rather than exact match technique. The major drawback of TCAM is high power consumption (12---15 Watts per chip) due to increase in lookup time. The objective of this paper was to reduce the search time of a key, which is stored in the forwarding table. This paper also proposes an efficient way to represent data and to reduce the index TCAM size by using $$y$$y-fast trie-partitioning algorithm, and it will take search time complexity of $$O(loglog~n)$$O(loglogn).

IP 주소 검색은 라우터에서 가장 중요하고 복잡한 기능중 하나이다. 본 논문에서는 고성능 라우터에서 IP 주소 검색의 성능을 향상시키기 위해 LC-trie를 개선하는 기법을 제안한다. TCAM(Ternary Content Addressable Memory)에서 테이블 압축을 위해 이용한 프리픽스 pruning 방법을 LC-trie에 효과적으로 적용한다. 이러한 기법은 메모리 참조 횟수를 감소시키고 검색의 속도를 높일 수 있다. 또한, 실제 사용되는 포워딩 테이블과 트래픽 분포를 사용하여 검색 시간과 메모리 참조 횟수 둥의 관점에서 개선된 기법의 성능을 기존의 LC-trie 기법과 비교 평가한다. IP address lookup is one of the most important and complex functions in the router. In this paper, we propose an improved technique of LC-trie to increase the performance of IP address lookup in the high performance router. We effectively apply the prefix pruning method, which is used for the compression of the forwarding table in TCAM((Ternary Content Addressable Memory), to the LC-trie. This technique can decrease the number of memory accesses and upgrade the lookup speed. Moreover, through the real forwarding table and the real traffic distribution, we evaluate the performance of our scheme in terms of the lookup time and the number of memory access, comparing with that of the previous LC-trie.