• The KIPS Transactions:PartA
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• v.17A no.5
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• pp.221-228
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• 2010

Since string operations were applied to computational biology, security and search for Internet, various data structures and algorithms for computing efficient string operations have been studied. The all-pairs suffix-prefix matching is to find the longest suffix and prefix among given strings. The matching algorithm is importantly used for fast approximation algorithm to find the shortest superstring, as well as for bio-informatics and data compressions. In this paper, we propose an algorithm to find all-pairs suffix-prefix matching using the suffix array, which takes O($k{\cdot}m$)�� time complexity. The suffix array algorithm is proven to be better than the suffix tree algorithm by showing it takes less time and memory through experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.3B
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• pp.65-71
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• 2005

The primary function of the Internet routers is to forward incoming packets toward their final destinations. IP address lookup is one of the most important functions in evaluating router performance since IP address lookup should be performed in wire-speed for the hundred-millions of incoming packets per second. With CIDR, the IP prefixes of routing table have arbitrary lengths, and hence address lookup by exact match is no longer valid. As a result, when packets arrive, routers compare the destination IP addresses of input packets with all prefixes in its routing table and determine the most specific entry among matching entries, and this is called the longest prefix matching. In this paper, based on parallel multiple hashing and prefix grouping, we have proposed a hardware architecture which performs an address lookup with a single memory access.

• The KIPS Transactions:PartA
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• v.11A no.2
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• pp.129-142
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• 2004

As the Internet gets faster, the demand for high-speed routers that are capable of forwarding more than giga bits of data per second keeps increasing. In the previous research, Bitmap Trie algorithm was developed to rapidly execute LPM(longest prefix matching) process which is Well known as the Severe performance bottleneck. In this paper, we introduce a novel algorithm that drastically enhanced the performance of Bitmap. Trie algorithm by applying three techniques. First, a new table called the Count Table was devised. Owing to this table, we successfully eliminated shift operations that was the main cause of performance degradation in Bitmap Trie algorithm. Second, memory utilization was improved by removing redundant forwarding information from the Transfer Table. Lastly. the range of prefix lookup was diversified to optimize data accesses. On the other hand, the processing delays were classified into three categories according to their causes. They were, then, measured through the execution-driven simulation that provides the higher quality of the results than any other simulation techniques. We tried to assure the reliability of the experimental results by comparing with those that collected from the real system. Finally the Enhanced Bitmap Trie algorithm reduced 82% of time spent in previous algorithm.

• ETRI Journal
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• v.33 no.3
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• pp.344-354
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• 2011

In this paper, a model is introduced named double relation chains (DRC) based on ordered sets. It is proved that using DRC and special relationships among the members of an alphabet, vectors of this alphabet can be stored and searched in a tree. This idea is general; however, one special application of DRC is the longest prefix matching (LPM) problem in an IP network. Applying the idea of DRC to the LPM problem makes the prefixes comparable like numbers using a pair of w-bit vectors to store at least one and at most w prefixes, where w is the IP address length. This leads to good compression performance. Based on this, two recently introduced structures called coded prefix trees and scalar prefix trees are shown to be specific applications of DRC. They are implementable on balanced trees which cause the node access complexity for prefix search and update procedures to be O(log n) where n is the number of prefixes. As another advantage, the number of node accesses for these procedures does not depend on w. Additionally, they need fewer number of node accesses compared to recent range-based solutions. These structures are applicable on both IPv4 and IPv6, and can be implemented in software or hardware.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.3-4
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• 2006

Fast IP address lookup in routers is essential to achieve packet forwarding in wire-speed. The longest prefix matching for IP address lookup is more complex than exact matching because of its dual dimensions, length and value. By thoroughly studying the current proposals for IP address lookup, we find out that the binary search could be a low-cost solution while providing high performance. Most of the existing binary search algorithms based on trie have simple data structures which can be easily implemented, but they have some problems because of empty internal nodes. The proposed algorithm is based on trie structure, but empty internal nodes are replaced by priority prefixes. The best-matching-prefix search in the proposed algorithm is more efficiently performed since search can be finished earlier when input is matched with a priority prefix. The performance evaluation results show that the constructed priority-trie has very good performance in the lookup speed and the scalability.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.11C
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• pp.43-50
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• 2001

The IP routing uses the longest-matching prefix to determine the destination. Fast lookup should be required for the high speed routing. We propose a modified LC-trie, called multiple LC-trie, which is suitable data structure for fast address-lookups in software implementation. To reduce the number of memory accesses, our scheme analyzes the distribution of IP address access pattern, and constructs multiple LC:-tries for frequently accessed IP addresses. Our experimental results show that our scheme can perform faster than the original LC-trie schemes.

• International journal of advanced smart convergence
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• v.5 no.3
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• pp.47-55
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• 2016

Router main task is to provide routing of Internet Protocol (IP) packets. Routing is achieved with help of the IP lookup. Router stores information about the networks and interfaces in data structures commonly called as routing tables. Comparison of IP from incoming packet with the IPs stored in routing table for the information about route is IP Lookup. IP lookup performs by longest IP prefix matching. The performance of the IP router is based on the speed of prefix matching. IP lookup is a major bottle neck in the performance of Router. Various algorithms and data structures are available for IP lookup. This paper is about reviewing various tree based structure and its performance evaluation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.11B
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• pp.911-919
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• 2004

IP address lookup is one of the essential functions on internet routers, and it determines overall router performance. The most important evaluation factor for software-based IP address lookup is the number of the worst case memory accesses. Binary prefix tree (BPT) scheme gives small number of worst case memory accesses among previous software-based schemes. However the tree structure of BPT is normally unbalanced. In this paper, we propose weighted binary prefix tree (WBP) scheme which generates nearly balanced tree, through combining the concept of weight to the BPT generation process. The proposed WBPT gives very small number of worst case memory accesses compared to the previous software-based schemes. Moreover the WBPT requires comparably small size of memory which can be fit within L2 cache for about 30,000 prefixes, and it is rather simple for prefix addition and deletion. Hence the proposed WBPT can be used for software-based If address lookup in practical routers.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10e
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• pp.1-3
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• 2002

백본 라우터에서의 최장 길이 프리픽스 검색(LPM: Longest Prefix Matching) 속도를 향상시키기 위해 활발히 연구된 방식들은 계산 량과 사용 메모리 량을 교환하는 방식들이다. 이러한 방식들은 성능향상을 위해서 대용량의 포워딩 테이블(Forwarding Table)을 캐쉬(Cache)에 저장할 수 있는 소용량 인덱스 테이블(Index Table)로 압축함으로써 고속 캐쉬 접근 회수와 그 계산량은 증가하는 대신 저속 메모리 접근 회수를 줄이는 방식이다.〔1〕본논문에서는 저속 메모리 사용량이 증가하는 반면 저속 메모리의 접근 빈도와 계산량을 동시에 감소시키는 FPLL(Fixed Prefix Length Lookup) 방식을 소개한다. 이 방식은 포워딩 엔트리(Entry)들을 프리픽스의 상위 비트(Bit)에 의해 그룹으로 나누고, 각 그룹에 속하는 엔트리들을 같은 길이로 정렬한다. FPLL에서의 LPM검색은 목적지 주소가 속하는 그룹들의 길이를 계산하여 검색할 최장 프리픽스의 길이를 미리 결정하고, 결정된 프리픽스를 키(key)로 하여 해시 테이블(Hash Table)로 구성된 포워딩 테이블에서 완전 일치(Exact Matching) 검색을 한다. 완전 일치 검색을 위해 같은 그룹에 속한 엔트리들을 정렬할 필요가 있는데 이 정렬을 위해 여분의 포워딩 테이블 엔트리가 생성된다. 3만개 엔트리를 갖는 Mae-West〔2〕 경우에, FPLL방식은 12만개 정도의 여분의 엔트리가 추가로 생성되는 대신에 1번 캐쉬 접근과 O(1)의 복잡도를 갖는 해시 테이블 검색으로 LPM 검색을 수행한다.

• Journal of KIISE:Information Networking
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• v.30 no.2
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• pp.282-292
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• 2003

This paper proposes an efficient data structure for forwarding IPv4 and IPv6 packets at the gigabit speed in backbone routers. The LPM(Longest Prefix Matching) search becomes a bottleneck of routers' performance since the LPM complexity grows in proportion to the forwarding table size and the address length. To speed up the forwarding process, this paper introduces a data structure named BMT(Bit-Map Tie) to minimize the frequent main memory accesses. All the necessary search computations in BMT are done over a small index table stored at cache. To build the small index table from the tie representation of the forwarding table, BMT represents a link pointer to the child node and a node pointer to the corresponding entry in the forwarding table with one bit respectively. To improve the poor performance of the conventional tries when their height becomes higher due to the increase of the address length, BMT adopts a binary search algorithm for determining the appropriate level of tries to start. The simulation experiments show that BMT compacts the IPv4 backbone routers' forwarding table into a small one less than 512-kbyte and achieves the average speed of 250ns/packet on Pentium II processors, which is almost the same performance as the fastest conventional lookup algorithms.