• Korean Journal of Computational Design and Engineering
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• v.22 no.2
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• pp.110-117
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• 2017

Delaunay refinement algorithm is a classical method to generate quality triangular meshes when point cloud and/or constrained edges are given in two- or three-dimensional space. It computes the Delaunay triangulation for given points and edges to obtain an initial solution, and update the triangulation by inserting steiner points one by one to get an improved quality triangulation. This process repeats until it satisfies given quality criteria. The efficiency of the algorithm depends on the criteria and point insertion method. In this paper, we propose a method to accelerate the Delaunay refinement algorithm by applying geometric hashing technique called bucketing when inserting a new steiner point so that it can localize necessary computation. We have tested the proposed method with a few types of data sets, and the experimental result shows strong linear time behavior.

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.93-96
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• 2021

The desire for a technology that can mechanically acquire 2D images starting with the manual method of drawing has been making possible a wide range of modern image-based technologies and applications over a period. Moreover, this trend of the utilization of image-related technology as well as image-based information is likely to continue. Naturally, as like other technology areas, the function that humans produce and utilize by using images needs to be automated by using computing-based technologies. Surprisingly, technology using images in the future will be able to discover knowledge that humans have never known before through the information-related process that enables new perception, far beyond the scope of use that human has used before. Regarding this trend, the manipulation and configuration of massively distributed image database system is strongly demanded. In this paper, we discuss image identifier production methods based on the utilization of the image hashing technique which especially puts emphasis over an entropy operator.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.584-587
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• 2021

일반적으로 얼굴인식 시스템은 영상에서 추출한 Feature와 DB 상의 Feature를 비교하는 구조를 가지고 있다. 하지만 원하는 Class의 Feature만 보고 DB 상에서 일치하는 Class의 위치를 특정하는 것은 불가능하기에 DB 상의 모든 Feature와 비교하는 절차가 필요하다. DB 크기가 커짐에 따라 처리시간과 메모리상의 문제가 발생하는데, 이 논문에서는 이를 해결하기 위한 Deep Hashing 모델을 제안한다. Softmax 기반의 Loss를 이용하여 학습하였고, 8-bits의 해시를 추출하였을 때 53%의 Feature 일치율을 보였으며, 이를 사용할 경우 DB 평균 대조군을 23% 이하로 줄이는 효과를 볼 수 있을 것으로 추정한다.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.6
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• pp.127-138
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• 2019

The data response speed is a critical issue of cloud services because it directly related to the user experience. As such, the in-memory database is widely adopted in many cloud-based applications for achieving fast data response. However, the current implementation of the in-memory database is mostly based on the linked list-based hash table which cannot guarantee the constant data response time. Thus, cuckoo hashing was introduced as an alternative solution, however, there is a disadvantage that only half of the allocated memory can be used for storing data. Subsequently, bucketized cuckoo hashing (BCH) improved the performance of cuckoo hashing in terms of memory efficiency but still cannot overcome the limitation that the insert overhead. In this paper, we propose a data management solution called Wall Cuckoo which aims to improve not only the insert performance but also lookup performance of BCH. The key idea of Wall Cuckoo is that separates the data among a bucket according to the different hash function be used. By doing so, the searching range among the bucket is narrowed down, thereby the amount of slot accesses required for the data lookup can be reduced. At the same time, the insert performance will be improved because the insert is following up the operation of the lookup. According to analysis, the expected value of slot access required for our Wall Cuckoo is less than that of BCH. We conducted experiments to show that Wall Cuckoo outperforms the BCH and Sorting Cuckoo in terms of the amount of slot access in lookup and insert operations and in different load factor (i.e., 10%-95%).

• Proceedings of the Korea Multimedia Society Conference
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• 2003.11a
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• pp.388-391
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• 2003

대규모의 대용량 파일 시스템에서 전통적인 파일 시스템인 UNIK와 같은 디렉토리 구조를 갖게 되면, 파일 탐색 시 순차 검색으로 인해 많은 시간이 걸리게 된다. 이러한 문제를 해결하고자, 본 논문에서는 파일의 수를 고려하여 파일의 수가 적을 때는 inode 블록에 디렉토리 엔트리를 함께 저장하고, 파일의 수가 많아져 inode 블록에서 오버플로우가 발생하면 선형 해싱(Linear Hashing)을 이용하여 디렉토리 엔트리를 저장하고자 한다 선형 해싱 디렉토리 구조의 설계 및 구현에 대해서 설명하고, 일반적으로 대용량 파일 시스템에서 많이 사용되는 B+ 트리 디렉토리 구조와 성능을 비교 분석한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.11a
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• pp.364-365
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• 2011

In this paper, we show that methods of perceptual image hashing which have been proposed recent years. And the disadvantages of them. Perceptual robustness, security and fragility are properties what we always discuss. Then we propose some ideas which we will do the research later.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.2B
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• pp.138-143
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• 2003

One of the important design issues for IP routers responsible for packet forwarding in computer networks is the route-lookup mechanism. For each incoming packet, IP routing requires that a router performs a longest-prefix-match address lookup in order to determine the next hop that the incoming packet should be forwarded to. In this paper, we present a new scheme which applies the hashing function for IP address lookup. In the proposed scheme, the forwarding table is composed of multiple SRAMs, and each SRAM represents an address lookup table in each prefix. Hashing function is applied in order to find out the matching entries from the address lookup tables in parallel, and the entry with the longest prefix match among them is selected. Simulation using the MAE-WEST router example shows that a large routing table with 37000 entries can be compacted to a forwarding table of 300 Kbytes in the proposed scheme. It is also shown that the proposed scheme achieves one route lookup every 1.93 memory accesses in average.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.5 s.347
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• pp.137-146
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• 2006

IP address lookup has become a major bottleneck of packet forwarding and a critical issue for high-speed networking techniques in routers. In this paper, we propose an efficient high-speed IP address lookup scheme using adaptive multiple hashing and prefix grouping. According to our analysis results based on routing data distributions, we grouped prefix lengths and selected the number of hash functions in each group adaptively. As a result, we can reduce collisions caused by hashing. Accordingly, a forwarding table of our scheme has good memory efficiency, and thus is organized with the proper number of memory modules. Also, the proposed scheme has the fast building and searching mechanisms to develop the forwarding table only during a single memory access.

• The KIPS Transactions:PartA
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• v.14A no.5
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• pp.269-278
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• 2007

Caching in a cache sorrel cluster environment has an advantage that minimizes the request and response tine of internet traffic and web user. Then, one of the methods that increases the hit ratio of cache is using the hash function with cooperative caching. It is keeping a fixed size of the total cache memory regardless of the number of cache servers. On the contrary, if there is no cooperative caching, the total size of cache memory increases proportional to the number of cache sowers since each cache server should keep all the cache data. The disadvantage of hashing method is that clients' requests stress a few servers in all the cache servers due to the characteristics of hashing md the overall performance of a cache server cluster depends on a few servers. In this paper, we propose the method that distributes uniformly client requests between cache servers using dynamic server information. We performed experiments using 16 PCs. Experimental results show the uniform distribution o

• 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.