• Proceedings of the Korean Information Science Society Conference
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• 2000.10a
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• pp.539-541
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• 2000

윈도우 방법과 인수분해 방법을 혼합 적용하면 멱승 연산에 사용되는 곱셈 연산의 횟수를 줄임으로써 멱승 연산을 빠르게 수행할 수 있다. 지수가 512비트일 때 윈도우의 크가 5인 윈도우 방법은 607번 정도의 곱셈 연산을 필요로 하는데 반해 윈도우와 인수분해 방법을 혼합한 방법은 599번 정도의 곱셈 연산을 필요로 한다. 이는 현실적으로 가능한 멱승 연산 중에서 가장 적은 수의 곱셈 연산을 요구하는 방법이다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.10 no.4
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• pp.73-79
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• 2000

We show how to reduce the number of multiplications required for an exponentiation by using a window method and a factor method. This method requires 599 multiplications for a 512-bit integer exponent while the window method with window size 5 requires 607 multiplications. This method requires fewest multiplications among practical exponentiation algo- rithms.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.3
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• pp.134-142
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• 2002

Quadtree, which is a hierarchical data structure, is a very important data structure to represent binary images. The linear quadtree representation as a way to store a quadtree is efficient to save space compared with other representations. Therefore, it has been widely studied to develop efficient algorithms to execute operations related with quadtrees. The window operation is one of important geometry operations in image processing, which extracts a sub-image indicated by a window in the image. In this paper, we present an algorithm to perform the window operation of binary images represented by quadtrees, using three-dimensional $n{\times}n{\times}n$ processors on RMESH(Reconfigurable MESH). This algorithm has constant-time complexity by using efficient basic operations to route the locational codes of quardtree on the hierarchical structure of $n{\times}n{\times}n$ RMESH.

• Journal of Korea Spatial Information System Society
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• v.9 no.2
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• pp.25-34
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• 2007

Existing approaches that select an order for the join of three or more data streams have always used the simple heuristics. For their disadvantage - only one factor is considered and that is join selectivity or arrival rate, these methods lead to poor performance and inefficiency In some applications. The graph-based sliding window multi -join algorithm with optimal join sequence is proposed in this paper. In this method, sliding window join graph is set up primarily, in which a vertex represents a join operator and an edge indicates the join relationship among sliding windows, also the vertex weight and the edge weight represent the cost of join and the reciprocity of join operators respectively. Then the optimal join order can be found in the graph by using improved MVP algorithm. The final result can be produced by executing the join plan with the nested loop join procedure, The advantages of our algorithm are proved by the performance comparison with existing join algorithms.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.11a
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• pp.417-420
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• 2006

스트림 데이터는 고속으로 생성되고 용량이 방대하여 저장하기 힘들며 데이터가 흘러가는 가운데 분석해야 하므로 기존 데이터 분석 방식을 그대로 사용하기는 어렵다. 본 연구에서는 스트림 데이터 분석 연산중의 하나인 다차원 집계 연산을 고속으로 처리하는 방법을 제안한다. 기존 연구들과 마찬가지로 스트림 데이터를 시간 차원 기준으로 윈도우 단위로 나누고, 각 윈도우마다 독립적인 집계 연산을 하도록 하였으며, 생성하고자 하는 집계 테이블들은 스트림 데이터가 입력되기 전에 미리 결정된다고 가정하였다. 정렬되지 않은 스트림 데이터를 고속으로 집계하기 위해 본 연구에서는 배열과 AVL 트리 구조를 혼합하여 사용하였다. 이 방법은 생성할 집계 테이블들 선택이 자유롭고, 집계 테이블들 전체가 메모리에 상주할 수 없을 정도로 큰 경우도 집계 연산을 실행할 수 있다는 장점을 갖는다. 제안한 방법의 효율성은 실험을 통해 입증하였다.

• The Journal of the Korea Contents Association
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• v.8 no.4
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• pp.48-54
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• 2008

This paper analyzes cost tradeoffs between memory usage and computation for window-based operators in data stream environments. It identifies generic operator network constructs, and sets up a cost model for the estimation of the expected memory reduction and the computation overheads when window memory relocations are applied to each operator network construct. This cost model helps to identify the utility of window memory relocations. It also helps to apply window memory relocation to improve a query execution plan to save memory usage. The proposed approach contributes to expand the scope of query processing and optimization in data stream environments. It also provides a basis to develop a cost estimation model for the query optimization using window memory relocations.

• Journal of the Korea Society of Computer and Information
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• v.17 no.2
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• pp.149-157
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• 2012

In this thesis, the problem of computing approximate answers to continuous sliding-window joins over data streams when the available memory may be insufficient to keep the entire join state. One approximation scenario is to provide a maximum subset of the result, with the objective of losing as few result tuples as possible. An alternative scenario is to provide a random sample of the join result, e.g., if the output of the join is being aggregated. It is shown formally that neither approximation can be addressed effectively for a sliding-window join of arbitrary input streams. Previous work has addressed only the maximum-subset problem, and has implicitly used a frequency based model of stream arrival. There exists a sampling problem for this model. More importantly, it is shown that a broad class of applications for which an age-based model of stream arrival is more appropriate, and both approximation scenarios under this new model are addressed. Finally, for the case of multiple joins being executed with an overall memory constraint, an algorithm for memory allocation across the join that optimizes a combined measure of approximation in all scenarios considered is provided.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.8B
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• pp.736-744
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• 2006

For the handhold devices, minimizing repetitive CPU operations such as multiplications is a major factor for their performances. In this paper, we propose efficient algorithms for finding similar sequences from streaming time-series data such as stock prices, network traffic data, and sensor network data. First, we formally define the problem of similar subsequence matching from streaming time-series data, which is called the stream sequence matching in this paper. Second, based on the window construction mechanism adopted by the previous subsequence matching algorithms, we present an efficient window-based approach that minimizes CPU operations required for stream sequence matching. Third, we propose a notion of window MBR and present two stream sequence matching algorithms based on the notion. Fourth, we formally prove correctness of the proposed algorithms. Finally, through a series of analyses and experiments, we show that our algorithms significantly outperform the naive algorithm. We believe that our window-based algorithms are excellent choices for embedded stream sequence matching in handhold devices.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 1998.12a
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• pp.329-333
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• 1998

대부분의 공개키 암호시스템은 큰 수의 모듈라 멱승을 기본으로 한다. 본 논문에서는 대표적인 고속 모듈라 멱승 알고리즘인 몽고메리법에 대해 윈도우법을 결합하여 연산한 결과효율성이 향상됨을 보였고, 이러한 결과를 윈도우법과 비교하여 실험하였다.

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.223-230
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• 2006

A window-based image processing is an elementary part of image processing area. Because window-based image processing is computationally intensive and data intensive, it is hard to perform ail of the operations of a window-based image processing in real-time by using a software program on general-purpose computers. This paper proposes a parallel hardware architecture that can perform a window-based image processing in real-time using FPGA(Field Programmable Gate Array). A dynamic threshold circuit and a local histogram equalization circuit of the proposed architecture are designed using VHDL(VHSIC Hardware Description Language) and implemented with an FPGA. The performances of both implementations are measured.