• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.103-108
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• 2023

We study the problem of selecting a subset of sensor nodes in sensor networks in order to maximize the performance of parameter estimation. To achieve a low-complexity sensor selection algorithm, we propose a greedy iterative algorithm that allows us to select one sensor node at a time so as to maximize the log-determinant of the inverse of the estimation error covariance matrix without resort to direct minimization of the estimation error. We apply QR factorization to the observation matrix in the log-determinant to derive an analytic selection rule which enables a fast selection of the next node at each iteration. We conduct the extensive experiments to show that the proposed algorithm offers a competitive performance in terms of estimation performance and complexity as compared with previous sensor selection techniques and provides a practical solution to the selection problem for various network applications.

• Journal of Korea Game Society
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• v.15 no.5
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• pp.109-118
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• 2015

The game of Go originated from ancient China is regarded as one of the most difficult challenges in the filed of AI. Over the past few years, the top computer Go programs based on MCTS have surprisingly beaten professional players with handicap. MCTS is an approach that simulates a random sequence of legal moves until the game is ended, and replaced the traditional knowledge-based approach. We applied the UCT algorithm which is a MCTS variant to the game of Tic-Tac-Toe for finding the best first move, and compared it with the result generated by a pure MCTS. Furthermore, we introduced and compared the performances of epsilon-Greedy algorithm and UCB algorithm for solving the Multi-Armed Bandit problem to understand the UCB.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1023-1030
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• 2020

We address the sampling set selection problem for arbitrary graph signals such that the original graph signal is reconstructed from the signal values on the nodes in the sampling set. We introduce a variation difference as a new indirect metric that measures the error of signal variations caused by sampling process without resorting to the eigen-decomposition which requires a huge computational cost. Instead of directly minimizing the reconstruction error, we propose a simple and fast greedy selection algorithm that minimizes the variation differences at each iteration and justify the proposed reasoning by showing that the principle used in the proposed process is similar to that in the previous novel technique. We run experiments to show that the proposed method yields a competitive reconstruction performance with a substantially reduced complexity for various graphs as compared with the previous selection methods.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.895-900
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• 2023

We study low-complexity graph sampling which selects a subset of nodes from graph nodes so as to reconstruct the original signal from the sampled one. To achieve complexity reduction, we propose a graph sampling algorithm with thresholding which selects a node with a cost lower than a given threshold at each step without fully searching all of the remaining nodes to find one with the minimum cost. Since it is important to find the threshold as close to a minimum cost as possible to avoid degradation of the reconstruction performance, we present a mathematical expression to compute the threshold at each step. We investigate the performance of the different sampling methods for various graphs, showing that the proposed algorithm runs 1.3 times faster than the previous method while maintaining the reconstruction performance.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10c
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• pp.223-225
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• 2002

Decision tree는 목표 데이터에 대한 계층적 관점을 보여준다는 의미에서 데이터를 보다 잘 이해하는데 많은 도움이 되나 탐욕법(greedy algorithm)에 의한 트리 생성법의 한계로 인해 최적의 예측자라고는 할 수가 없다. 이와 같은 약점을 보완하기 위하여 일반적 방법으로 생성한 decision tree에 대하여 다차원 연관규칙 알고리즘을 적용함으로써 짱은 길이의 최적 부분 규칙집합을 구하는 방법을 제시하였고 실험을 통해 그와 같은 사실을 확인하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.706-709
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• 2015

영향력 전파 문제는 주어진 네트워크 환경에서 영향력을 최대화 할 수 있는 top-k 노드를 찾는 문제로 데이터 마이닝 분야에서 활발히 연구되어왔다. 본 논문에서는 그래프 클러스터링 기법을 사용하여 영향력을 전파하는 방법을 제안하고자 한다. 이러한 방법에는 두 가지 이점이 있는데 먼저 서로 다른 시드 사이에 영향력이 중복되는 블로킹 현상을 제거하여 수행시간을 단축시킬 수 있다. 다음으로는 유 방향 그래프인 경우 기존의 탐욕 알고리즘보다 더 많은 노드에 전파를 가능하게 한다.

• The Journal of the Korea Contents Association
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• v.10 no.5
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• pp.1-9
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• 2010

This paper propose a novel scheme called selective evaluation to improve convergence of ACO (ant colony optimization) for feature selection. The scheme cutdown the computational load by excluding the evaluation of unnecessary or less promising candidate solutions. The scheme is realizable in ACO due to the valuable information, pheromone trail which helps identify those solutions. With the aim of checking applicability of algorithms according to problem size, we analyze the timing requirements of three popular feature selection algorithms, greedy algorithm, genetic algorithm, and ant colony optimization. For a rigorous timing analysis, we adopt the concept of atomic operation. Experimental results showed that the ACO with selective evaluation was promising both in timing requirement and recognition performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.9
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• pp.1719-1721
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• 2015

In this paper, we investigate a frequency assignment problem from graph theory for military communications. We propose an algorithm based on the graph coloring theory and confirm that we utilize 0.77 times lower number of frequencies. We also propose a hybrid algorithm that facilitates a trade-off between the range and the spectrum utilization gain.

• 한국벤처창업학회:학술대회논문집
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• 2010.08a
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• pp.71-89
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• 2010

It is strongly believed that multicast will become one of the most promising services on internet for the next generation. Multicast service can be deployed either on network-layer or application-layer. IP multicast (network-layer multicast) is implemented by network nodes (i.e., routers) and avoids multiple copies of the same datagram on the same link. Despite the conceptual simplicity of IP multicast and its obvious benefits, it has not been widely deployed since there remain many unresolved issues. As an alternative to IP multicast, overlay multicast (application-layer multicast) implements the multicast functionality at end hosts rather than routers. This may require more overall bandwidth than IP multicast because duplicate packets travel the same physical links multiple times, but it provides an inexpensive, deployable method of providing point-to-multipoint group communication. In this paper we develop an efficient method applied greedy algorithm for solving two models of overlay multicast tree building problem that is aimed to construct MDST (Minimum Diameter Spanning Tree : minimum cost path from a source node to all its receivers) and MST (Minimum Spanning Tree : minimum total cost spanning all the members). We also simulate and analyze MDST and MST.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.165-170
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• 2023

This paper proposes an algorithm that can obtain a solution with linear time for a set cover problem(SCP) in which there is no polynomial time algorithm as an NP-complete problem so far. Until now, only heuristic greed algorithms are known to select sets that can be covered to the maximum. On the other hand, the proposed algorithm is a competitive algorithm that applies an inclusion-exclusion principle rule to N nodes up to 2nd or 3rd in the maximum number of elements to obtain a set covering all k nodes, and selects the minimum cover set among them. The proposed algorithm compensated for the disadvantage that the greedy algorithm does not obtain the optimal solution. As a result of applying the proposed algorithm to various application cases, an optimal solution was obtained with a polynomial time of O(kn²).