• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.11B
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• pp.1285-1296
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• 2011

Packet classification is one of the basic and important functions of the Internet routers, and it became more important along with new emerging application programs requiring real-time transmission. Since packet classification should be accomplished in line-speed on each incoming input packet for multiple header fields, it becomes one of the challenges in designing Internet routers. Various packet classification algorithms have been proposed to provide the high-speed packet classification. Hierarchical approach achieves effective packet classification performance by significantly narrowing down the search space whenever a field lookup is completed. However, hierarchical approach involves back-tracking problem. In order to solve the problem, set-pruning trie and grid-of-trie algorithms are proposed. However, the algorithm either causes excessive node duplication or heavy pre-computation. In this paper, we propose a smart set-pruning trie which reduces the number of node duplication in the set-pruning trie by the simple merging of the lower-level tries. Simulation result shows that the proposed trie has the reduced number of copied nodes by 2-8% compared with the set-pruning trie.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.15-16
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• 2007

In order to provide value-added services, next generation routers should perform packet classification for each incoming packet at wire-speed. In this paper, we proposed hierarchical priority trio (Hptrie) for packet classification. The proposed scheme improves the search performance and the memory requirement by replacing empty internal nodes in ordinary hierarchical trio with priority nodes which are the nodes including the highest priority rule among sub-trie nodes.

• Journal of the Korea Society of Computer and Information
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• v.12 no.4
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• pp.11-19
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• 2007

This paper proposes RCB(Reduced Compact Binary) tie to correct faults of both CB(Compact Binary) tie and HCB(Hierarchical Compact Binary) trie. First, in the case of CB trie, a compact structure was tried for the first time, but as the amount of data was increasing, that of inputted data gained and much difficulty was experienced in insertion due to the dummy nods used in balancing trees. On the other hand, if the HCB trie realized hierarchically, given certain depth to prevent the map from increasing on the right, reached the depth, the method for making new trees and connecting to them was used. Eventually, fast progress could be made in the inputting and searching speed, but this had a disadvantage of the storage space becoming bigger because of the use of dummy nods like CB trie and of many tree links. In the case of RCB trie in this thesis, the tree-map could be reduced by about 35% by completely cutting down dummy nods and the whole size by half, compared with the HCB trie.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.365-371
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• 2015

CB tree represents the binary trie by a compact binary sequence. However, retrieval time grows fast since the more keys stored in the trie, longer the binary sequences are. In addition it is inefficient for frequent key insertion/deletion. HCB tree is a hierarchical CB tree consisting of small binary tries. However it can not avoid shift operations and have to scan an additional table to refer child or parent trie. In order to improve retrieval performance and avoid shift operations when keys are inserted or deleted, we in this paper represent each separated trie by a full binary trie and then assign the unique identifier to it. Finally the theoretical evaluations show that both the proposed approach and HCB tree provides better than CB tree for key retrieval. The proposed approach shows the highest performance in case of key insertion/deletion and moreover requires only 71%~89% of storage as compared with CB tree.

• Journal of Creative Information Culture
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• v.5 no.3
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• pp.345-353
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• 2019

Several studies have been proposed to improve storage space efficiency by expressing binary trie data structure as a linear binary bit string. Compact binary tree approach generated using one binary trie increases the key search time significantly as the binary bit string becomes very long as the size of the input key set increases. In order to reduce the key search range, a hierarchical compact binary tree technique that hierarchically expresses several small binary compact trees has been proposed. The search time increases proportionally with the number and length of binary bit streams. In this paper, we generate several binary compact trees represented by full binary tries hierarchically. The search performance is improved by allowing a path for the binary bit string corresponding to the search range to be determined through simple numeric conversion. Through the performance evaluation using the worst time and space complexity calculation, the proposed method showed the highest performance for retrieval and key insertion or deletion. In terms of space usage, the proposed method requires about 67% ~ 68% of space compared to the existing methods, showing the best space efficiency.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.3B
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• pp.143-152
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• 2007

In order to provide new value-added services such as a policy-based routing and the quality of services in next generation network, the Internet routers need to classify packets into flows for different treatments, and it is called a packet classification. Since the packet classification should be performed in wire-speed for every packet incoming in several hundred giga-bits per second, the packet classification becomes a bottleneck in the Internet routers. Therefore, high speed packet classification algorithms are required. In this paper, we propose an efficient packet classification architecture based on a hierarchical binary search fee. The proposed architecture hierarchically connects the binary search tree which does not have empty nodes, and hence the proposed architecture reduces the memory requirement and improves the search performance.