• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제2권5호
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• pp.191-198
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• 2013

이동하는 베이스 노드를 가진 무선 센서 네트워크(WSN)에서 실시간 침입탐지를 위해서는 침입을 탐지한 센서로부터 베이스 노드까지의 정보 전달이 짧은 라우팅 경로를 통해 이루어져야 한다. 센서 네트워크에서 최소 Wiener수 신장트리(MWST)기반 라우팅 방법은 최소 신장트리(MST)기반 라우팅 방법에 비해 작은 홉 수를 보장하고 있어서 실시간 침입탐지에 적합함이 알려져 있다. 하지만 주어진 네트워크로부터 최소 Wiener 수 신장트리를 찾는 문제는 NP-hard이고 특정 노드에 대한 의존성이 커서 최소 신장 트리 기반 라우팅 방법에 비해 짧은 네트워크 수명을 갖는 단점이 있다. 본 논문은 실시간 침입탐지를 위해 최소 Wiener수 신장트리를 개선해 작은 홉 수와 긴 네트워크의 수명을 동시에 보장하는 라우팅 트리를 찾는 다목적 개미 군집 최적화 알고리즘을 제안한다. 그리고 제안한 라우팅 트리의 성능을 패킷의 평균 전송 홉 수 및 네트워크 전력 소모, 네트워크의 수명 측면에서 최소 신장트리기반 라우팅 방법 및 최소 Wiener수 신장트리기반 라우팅 방법과 비교한다.

• 한국통신학회논문지
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• 제41권4호
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• pp.467-478
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• 2016

본 논문에서는 PS-LTE(Public Safety-Long Term Evolution) 환경에서 단독기지국의 설치에 있어서 전체 사용자의 데이터 처리량을 최대화하는 PSO(Particle Swarm Optimization)기반의 최적기지국 위치 선정 방법을 제안한다. 또한 전체 재난 지역을 탐색하여 최적의 위치를 찾는 완전탐색(Exhaustive Search) 방법, 임의보행(Random Walk) 이동모형을 적용하여 위치를 선정하는 방법, 기지국 균일 배치방법과의 성능을 비교하였다. 제안하는 방법의 경우 모든 지역을 탐색하여 최적위치를 찾는 완전탐색 방법과 유사한 최적위치 및 전체 사용자의 데이터 처리량(Throughput)을 갖지만, 최적해 수렴시간에 있어서 완전탐색의 경우 재난지역의 크기가 커질수록 증가하지만, 제안하는 방법 경우 빠른 수렴 시간 및 거의 일정한 수렴시간을 갖는 것을 알 수 있다.

• Current Optics and Photonics
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• 제5권4호
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• pp.431-443
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• 2021

Sparse unmixing has been proven to be an effective method for hyperspectral unmixing. Hyperspectral images contain rich spectral and spatial information. The means to make full use of spectral information, spatial information, and enhanced sparsity constraints are the main research directions to improve the accuracy of sparse unmixing. However, many algorithms only focus on one or two of these factors, because it is difficult to construct an unmixing model that considers all three factors. To address this issue, a novel algorithm called multiview-based spectral weighted and low-rank row-sparsity unmixing is proposed. A multiview data set is generated through spectral partitioning, and then spectral weighting is imposed on it to exploit the abundant spectral information. The row-sparsity approach, which controls the sparsity by the l_2,0 norm, outperforms the single-sparsity approach in many scenarios. Many algorithms use convex relaxation methods to solve the l_2,0 norm to avoid the NP-hard problem, but this will reduce sparsity and unmixing accuracy. In this paper, a row-hard-threshold function is introduced to solve the l_2,0 norm directly, which guarantees the sparsity of the results. The high spatial correlation of hyperspectral images is associated with low column rank; therefore, the low-rank constraint is adopted to utilize spatial information. Experiments with simulated and real data prove that the proposed algorithm can obtain better unmixing results.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1993년도 추계학술대회발표논문집; 서강대학교, 서울; 25 Sep. 1993
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• pp.12-19
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• 1993

In general, the line balancing problem is defined as of finding an assignment of the given jobs to the workstations under the precedence constraints given to the set of jobs. Usually, the objective is either minimizing the cycle time under the given number of workstations or minimizing the number of workstations under the given cycle time. In this paper, we present a new type of an assembly line balancing problem which occurs in an electronics company manufacturing home appliances. The main difference of the problem compared to the general line balancing problem lies in the structure of the precedence given to the set of jobs. In the problem, the set of jobs is partitioned into two disjoint subjects. One is called the set of fixed jobs and the other, the set of floating jobs. The fixed jobs should be processed in the linear order and some pair of the jobs should not be assigned to the same workstations. Whereas, to each floating job, a set of ranges is given. The range is given in terms of two fixed jobs and it means that the floating job can be processed after the first job is processed and before the second job is processed. There can be more than one range associated to a floating job. We present a procedure to find an approximate solution to the problem. The procedure consists of two major parts. One is to find the assignment of the floating jobs under the given (feasible) assignment of the fixed jobs. The problem can be viewed as a constrained bin packing problem. The other is to find the assignment of the whole jobs under the given linear precedence on the set of the floating jobs. First problem is NP-hard and we devise a heuristic procedure to the problem based on the transportation problem and matching problem. The second problem can be solved in polynomial time by the shortest path method. The algorithm works in iterative manner. One step is composed of two phases. In the first phase, we solve the constrained bin packing problem. In the second phase, the shortest path problem is solved using the phase 1 result. The result of the phase 2 is used as an input to the phase 1 problem at the next step. We test the proposed algorithm on the set of real data found in the washing machine assembly line.

• 지능정보연구
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• 제16권3호
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• pp.121-145
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• 2010

매 학기마다 반복되는 대학의 강의시간표 작성 방법은 대학 상황에 따라 다르며, 교육환경의 변화에 따라 그 복잡도와 문제의 크기가 증가되는 NP-hard 문제로 알려져 있다. 그 동안, 효과적인 강의자원 배분을 위한 강의시간표 자동생성의 필요성으로 대학 강의시간표 작성에 관한 여러 방법의 연구가 진행되어 왔다. 일반적으로 교양과목 강의시간표는 대학행정부서에서, 전공과목은 학과에서 작성하는데 각 학과 단위의 전공강의시간표작성지원시스템은 학생들의 편의를 도모하고 수업의 효과와 전공강의자원의 효과적인 배분를 위해 중요한 역할을 한다. 이를 위하여 본 연구는 한신대학교의 새로운 강의시간표 작성체계에 따라, 사례 기반의 템플릿을 생성하고, 이로부터 규칙 기반의 상호대화형으로 효과적인 강의자원 배분이 가능한 전공강의시간표를 작성하는 두 단계 지원시스템을 제안하였으며, 사례 데이터를 이용한 프로토타입으로 그 효과를 검정하였다. 과거 사례와의 유사도는 학과 평균 41.72%로 템플릿의 유용성을 볼 수 있으며, 민감도 분석 결과에서 동일 시간 개설과목 허용 임계치를 90% 이상 설정한다면 강의시간표가 더 고른 분포를 갖게 됨을 검정하였다.

• Journal of Communications and Networks
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• 제16권3호
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• pp.335-343
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• 2014

This paper considers the crucial problem of deploying wireless relays for achieving a connected wireless sensor network in indoor environments, an important aspect related to the management of the sensor network. Several algorithms have been proposed for ensuring full sensing coverage and network connectivity. These algorithms are not applicable to indoor environments because of the complexity of indoor environments, in which a radio signal can be dramatically degraded by obstacles such as walls. We first prove theoretically that the indoor relay placement problem is NP-hard. We then predict the radio coverage of a given relay deployment in indoor environments. We consider two practical scenarios; wire-connected relays and radio-connected relays. For the network with wire-connected relays, we propose an efficient greedy algorithm to compute the deployment locations of relays for achieving the required coverage percentage. This algorithm is proved to provide a $H_n$ factor approximation to the theoretical optimum, where $H_n=1+{\frac{1}{2}}+{\cdots}+{\frac{1}{n}}={\ln}(n)+1$, and n is the number of all grid points. In the network with radio-connected relays, relays have to be connected in an ad hoc mode. We then propose an algorithm based on the previous algorithm for ensuring the connectivity of relays. Experimental results demonstrate that the proposed algorithms achieve better performance than baseline algorithms.

• Molecules and Cells
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• 제27권3호
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• pp.271-277
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• 2009

Proteins interact with each other within a cell, and those interactions give rise to the biological function and dynamical behavior of cellular systems. Generally, the protein interactions are temporal, spatial, or condition dependent in a specific cell, where only a small part of interactions usually take place under certain conditions. Recently, although a large amount of protein interaction data have been collected by high-throughput technologies, the interactions are recorded or summarized under various or different conditions and therefore cannot be directly used to identify signaling pathways or active networks, which are believed to work in specific cells under specific conditions. However, protein interactions activated under specific conditions may give hints to the biological process underlying corresponding phenotypes. In particular, responsive functional modules consist of protein interactions activated under specific conditions can provide insight into the mechanism underlying biological systems, e.g. protein interaction subnetworks found for certain diseases rather than normal conditions may help to discover potential biomarkers. From computational viewpoint, identifying responsive functional modules can be formulated as an optimization problem. Therefore, efficient computational methods for extracting responsive functional modules are strongly demanded due to the NP-hard nature of such a combinatorial problem. In this review, we first report recent advances in development of computational methods for extracting responsive functional modules or active pathways from protein interaction network and microarray data. Then from computational aspect, we discuss remaining obstacles and perspectives for this attractive and challenging topic in the area of systems biology.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권12호
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• pp.4343-4355
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• 2014

Multicast group communication has many advantages in data centers and thus is widely used by many applications. It can efficiently reduce the network traffic and improve the application throughput. For the multicast application in data centers, an essential problem is how to find a minimal multicast tree, which has been proved to be NP-hard. In this paper, we propose an approximation tree-building method for the minimal multicast problem, named HD（Hamming Distance）-based multicast tree. Consider that many new network structures have been proposed for data centers. We choose three representative ones, including BCube, FBFLY, and HyperX, whose topological structures can be regarded as the generalized hypercube. Given a multicast group in BCube, the HD-based method can jointly schedule the path from each of receiver to the only sender among multiple disjoint paths; hence, it can quickly construct an efficient multicast tree with the low cost. The experimental results demonstrate that our method consumes less time to construct an efficient multicast tree, while considerably reduces the cost of the multicast tree compared to the representative methods. Our approach for BCube can also be adapted to other generalized hypercube network structures for data centers after minimal modifications.

• 산업경영시스템학회지
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• 제40권4호
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• pp.203-210
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• 2017

Data clustering is one of the most difficult and challenging problems and can be formally considered as a particular kind of NP-hard grouping problems. The K-means algorithm is one of the most popular and widely used clustering method because it is easy to implement and very efficient. However, it has high possibility to trap in local optimum and high variation of solutions with different initials for the large data set. Therefore, we need study efficient computational intelligence method to find the global optimal solution in data clustering problem within limited computational time. The objective of this paper is to propose a combined artificial bee colony (CABC) with K-means for initialization and finalization to find optimal solution that is effective on data clustering optimization problem. The artificial bee colony (ABC) is an algorithm motivated by the intelligent behavior exhibited by honeybees when searching for food. The performance of ABC is better than or similar to other population-based algorithms with the added advantage of employing fewer control parameters. Our proposed CABC method is able to provide near optimal solution within reasonable time to balance the converged and diversified searches. In this paper, the experiment and analysis of clustering problems demonstrate that CABC is a competitive approach comparing to previous partitioning approaches in satisfactory results with respect to solution quality. We validate the performance of CABC using Iris, Wine, Glass, Vowel, and Cloud UCI machine learning repository datasets comparing to previous studies by experiment and analysis. Our proposed KABCK (K-means+ABC+K-means) is better than ABCK (ABC+K-means), KABC (K-means+ABC), ABC, and K-means in our simulations.

• Journal of Communications and Networks
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• 제18권4호
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• pp.559-566
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• 2016

Software defined network (SDN) can effectively improve the performance of traffic engineering and will be widely used in backbone networks. Therefore, new energy-saving schemes must take SDN into consideration; this action is extremely important owing to the rapidly increasing energy consumption in telecom and Internet service provider (ISP) networks. Meanwhile, the introduction of SDN in current networks must be incremental in most cases, for technical and economic reasons. During this period, operators must manage hybrid networks in which SDN and traditional protocols coexist. In this study, we investigate the energy-efficient traffic engineering problem in hybrid SDN/Internet protocol (IP) networks. First, we formulate the mathematical optimization model considering the SDN/IP hybrid routing mode. The problem is NP-hard; therefore, we propose a fast heuristic algorithm named hybrid energy-aware traffic engineering (HEATE) as a solution. In our proposed HEATE algorithm, the IP routers perform shortest-path routing by using distributed open shortest path first (OSPF) link weight optimization. The SDNs perform multipath routing with traffic-flow splitting managed by the global SDN controller. The HEATE algorithm determines the optimal setting for the OSPF link weight and the splitting ratio of SDNs. Thus, the traffic flow is aggregated onto partial links, and the underutilized links can be turned off to save energy. Based on computer simulation results, we demonstrate that our algorithm achieves a significant improvement in energy efficiency in hybrid SDN/IP networks.