• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.527-531
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• 2012

In this paper, a novel DPSO-QI (Distributed PSO with quantum-infusion mechanism) algorithm improving one of the fatal defect, the so-called premature convergence, that degrades the performance of the conventional PSO algorithms is proposed. The proposed scheme has the following two distinguished features. First, a concept of neighborhood of each particle is introduced, which divides the whole swarm into several small groups with an appropriate size. Such a strategy restricts the information exchange between particles to be done only in each small group. It thus results in the improvement of particles' diversity and further minimization of a probability of occurring the premature convergence phenomena. Second, a quantum-infusion (QI) mechanism based on the quantum mechanics is introduced to generate a meaningful offspring in each small group. This offspring in our PSO mechanism improves the ability to explore a wider area precisely compared to the conventional one, so that the degree of precision of the algorithm is improved. Finally, some numerical results are compared with those of the conventional researches, which clearly demonstrates the effectiveness and reliability of the proposed DPSO-QI algorithm.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.6
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• pp.383-394
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• 2013

As a way of augmenting constrained resources of mobile devices such as CPU and memory, many works on mobile cloud computing (MCC), where mobile devices utilize remote resources of cloud services or PCs, have been proposed. Typically, in MCC, many nodes with different operating systems and platform and diverse mobile applications or services are located, and a central manager autonomously performs several management tasks to maintain a consistent level of MCC overall quality. However, as there are a larger number of nodes, mobile applications, and services subscribed by the mobile applications and their interactions are extremely increased, a traditional management method of MCC reveals a fundamental problem of degrading its overall performance due to overloaded management tasks to the central manager, i.e. a bottle neck phenomenon. Therefore, in this paper, we propose a clustering-based optimization method to solve performance-related problems on large-scaled MCC and to stabilize its overall quality. With our proposed method, we can ensure to minimize the management overloads and stabilize the quality of MCC in an active and autonomous way.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.9
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• pp.11-19
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• 2006

Design program was developed to determine the external shape of the supersonic axisymmetric inlet by combining conical flow solver and approximation technique of conical shock with gradient-based optimization algorithm. Inlet designs were carried out under various operation conditions through optimization with respectively two object functions which consist of pressure recovery and cowl drag and with constraints about shock position, cowl shape, and minimum throat area. New object function consisting of pressure recovery and drag of the external cowl was proposed and the optimized shapes from new object function were compared to the ones from the old object function which maximize only the pressure recovery. Through computations of inviscid and turbulent flow, was tested performance of the design program and performance estimated in design program agreed well with computation results for inlets designed under various flight conditions.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.48-51
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• 2022

정보통신기술의 (ICT) 발전에 따라 기업은 사용자에게 다양한 서비스를 제공하기 위해 클라우드 서비스 공급자의 클라우드를 활용하고 있다. 클라우드 서비스 공급자는 기업에게 전문적이고 효율적인 클라우드 서비스를 제공하고, 기업은 특별한 클라우드 설치 없이 제공받은 서비스를 활용하여 다양한 서비스를 제공할 수 있다. 최근 클라우드 서비스를 이용하는 기업이 세계적으로 증가함에 따라 클라우드 공급자는 효과적인 서비스를 제공하기 위해 다양한 클라우드 컴퓨팅 기술을 적용하고 있다. 클라우드를 사용하는 기업이 증가함에 따라 클라우드 서버의 수가 증가하고 있으며, 그 중에 해킹을 당하기 때문에 악의적인 노드가 되거나 어떤 불가피한 원인으로 저성능 노드가 되는 경우의 수도 증가하고 있다. 악의적인 노드는 사용자의 보안을 위협하며, 저성능 노드는 효과적인 서비스를 사용자에게 제공할 수 없다. 따라서 서비스 사용자는 다양한 클라우드 서버 중 사용자 수요에 최적화 된 클라우드 노드를 선택하는 기술이 필요하다. 본 논문에서는 효율적인 클라우드 컴퓨팅을 위한 스마트 계약 기반의 노드 선택 기법을 제안한다. 제안하는 노드 선택 기법은 스마트 계약에 따라 사용자가 원하는 서비스에 적합한 클라우드 서버를 선택할 수 있도록 하여 최적화된 클라우드 서비스를 제공한다. 동시에 클라우드 서버들에게 명예 등급에 부여하고 명예 등급이 높을수록 선택되는 확률이 증가한다. 결과적으로 사용자는 효과적인 클라우드 서비스를 선택할 수 있어 효과적인 클라우드 서비스 활용이 가능하다.

• The Journal of Society for e-Business Studies
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• v.23 no.1
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• pp.37-45
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• 2018

The current system upon which a variety of programs are in operation has continuously expanded its domain from conventional single-core and multi-core system to many-core and heterogeneous system. However, existing researches have focused mostly on parallelizing programs based CUDA framework and rarely on AMD based GCN-GPU optimization. In light of the aforementioned problems, our study focuses on the optimization techniques of the GCN architecture in a GPGPU environment and achieves a performance improvement. Specifically, by using performance techniques we propose, we have reduced more then 30% of the computation time of matrix multiplication and convolution algorithm in GPGPU. Also, we increase the kernel throughput by more then 40%.

• Korean Journal of Optics and Photonics
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• v.8 no.2
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• pp.88-94
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• 1997

Photographic lenses and an aspheric optical pickup-lens are designed by using damped least-squares(DLS) method. We start optimization with arbitrary initial damping factor. To improve the rate of convergence and the stability in optimization, we apply the special procedure that estimates numerical adequacy of derivative increments of variables to the DLS method. When the initial damping factor is almost equal to the median of series of eigenvalues, the convergence and the stability of the method significantly are improved. Optimized lenses have the performance of each target.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.539-544
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• 2003

The weapon-target assignment problem is solved using a genetic algorithm in this paper. The weapon-target assignment is an optimization problem which minimizes damages from enemy s attack or maximizes the kill probability of targets. Genetic algorithm is applied in this paper since it usually converges to a near global optimal solution. A specific structure of genetic algorithm which is suitable for the weapon-target assignment problem is proposed. A guideline selecting associated parameters is investigated through simulations. Comparition of the proposed method with several traditional optimization techniques for the weapon-target assignment problem shows the validity of the proposed method.

• Journal of Korean Association for Spatial Structures
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• v.7 no.5
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• pp.67-74
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• 2007

The unsymmetrically layered artificial material model is consistently introduced to find the optimum topologies of the plate structures. Reissner-Mindlin (RM) plate theory is adopted to formulate the present 9-node plate element considering the first-order shear deformation of the plates. In the topology optimization process, the strain energy to be minimized is employed as the objective function and the initial volume of structures is adopted as the constraint function. In addition, the resizing algorithm based on the optimality criteria is used to update the hole size introduced in the proposed artificial material model. Several numerical examples are rallied out to investigate the performance of the proposed technique. From numerical results, the proposed topology optimization techniques are found to be very effective to produce the optimum topology of plate structures. In particular, the proposed unsymmetric stiffening layer model make it possible to produce more realistic stiffener design of the plate structures.

• Journal of the Korea Society for Simulation
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• v.26 no.3
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• pp.55-63
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• 2017

In R&D of artillery system, error budget method is used to predict artillery firing error without field firing test. The error budget method for artillery has been consistently developed but apply for practical R&D of the weapon system has been avoided because of lacks of error budget source information. The error budget source is composed of every detailed error components which affect total distance and deflection error of artillery, and most of them are difficult to be calculated or measured. Also with the inaccuracy of source information, simulated error result dose not reflect real firing error. To resolve that problem, an optimization algorithm is adopted to figure out error budget sources from existing filed firing test. The method of finding input parameter estimation which is commonly used in aerodynamics was applied. As an optimization algorithm, CMA-ES is used and presented in the paper. The error budget sources which are figured out by the presented method can be applied to compute ROC of new weapon systems and may contribute to an improvement of accuracy in artillery.

• Journal of the Korea Society of Computer and Information
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• v.15 no.9
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• pp.47-55
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• 2010

Linear constraint satisfaction optimization problem is a kind of combinatorial optimization problem involving linearly expressed objective function and complex constraints. Integer programming is known as a very effective technique for such problem but require very much time and memory until finding a suboptimal solution. In this paper, we propose a method to improve the search performance by integrating local search and integer programming. Basically, simple hill-climbing search, which is the simplest form of local search, is used to solve the given problem and integer programming is applied to generate a neighbor solution. In addition, constraint programming is used to generate an initial solution. Through the experimental results using N-Queens maximization problems, we confirmed that the proposed method can produce far better solutions than any other search methods.