• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.4081-4098
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• 2022

With the aim of tackling the contradiction between computation intensive industrial applications and resource-weak Edge Devices (EDs) in Industrial Internet of Things (IIoT), a novel computation task offloading scheme in SDIN-enabled MEC based IIoT is proposed in this paper. With the aim of reducing the task accomplished latency and energy consumption of EDs, a joint optimization method is proposed for optimizing the local CPU-cycle frequency, offloading decision, and wireless and computation resources allocation jointly. Based on the optimization, the task offloading problem is formulated into a Mixed Integer Nonlinear Programming (MINLP) problem which is a large-scale NP-hard problem. In order to solve this problem in an accessible time complexity, a sub-optimal algorithm GPCOA, which is based on hybrid evolutionary computation, is proposed. Outcomes of emulation revel that the proposed method outperforms other baseline methods, and the optimization result shows that the latency-related weight is efficient for reducing the task execution delay and improving the energy efficiency.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.3A
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• pp.231-239
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• 2002

This paper presents a new fractal coding scheme to find sub-optimal transformation by performing an iterative encoding process. An optimal transformation can be defined as the transformation generating the attractor which is closest to an original image. Unfortunately, it has been well-known that it is actually impossible to find the optimal transformation due to heavy computation. In this paper, however, by means of some new theorems related with the fractal transformation due the attractor, it is shown that for a special case the optimal transformation can be obtained as well as for a general case the sub-optimal transformation. The proposed method based on the theorems obtains the sub-optimal transformation performing an iterative process as if done in decoding. Thus, it requires more computation than the conventional method but improves the image quality. We verify the superiority of the proposed method through the experimental results fur real images, which shows that the proposed method approaches to the optimal method in the performance and is superior to the conventional method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.771-777
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• 1996

In this paper, an optimal design technique for a Stewart platform has been presented considering workspace and dexterity. In the definition of a design objective function, previously suggested dexterity index was used to be maximized. In this optimal design process, the workspace can be used as design constraint when necessary. An algorithm for workspace computation has been briefly described. Finally, optimal desigm results for some example cases have been presented.

• Journal of Electrical Engineering and Technology
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• v.1 no.4
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• pp.455-460
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• 2006

This paper presents the convergency property of the Auxiliary Problem Principle when it is applied to large-scale Optimal Power Flow problems with Distributed or Parallel computation features. The key features and factors affecting the convergence ratio and solution stability of APP are also analyzed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.4
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• pp.188-194
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• 2014

V2I(Vehicular to Infrastructure) is a one kind of communication systems which is used between the base stations and mobile objects. In V2I communication system, it is difficult to obtain the desired communication performance. Beamforming technology is to find the optimal path. and it can be improved the communication performance. MUSIC algorithm can be estimated the direction of arrival. The directional vector of received signals and the eigenvector has orthogonal property. MUSIC algorithm uses this property. In V2I communication environment, real time optimal path is changed. By the high computational complexity of the MUSIC algorithm, the optimal path estimation error is generated. In this paper, we propose a method of computation reduction algorithm for MUSIC algorithm.

• Korean Journal of Computational Design and Engineering
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• v.15 no.5
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• pp.354-361
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• 2010

The paper presents an efficient computation of optimal tool length for 5-axis mold & die machining. The implemented procedure processes an NC file as an initial input, where the NC data is generated by another commercial CAM system. A commercial CAM system generates 5-axis machining NC data which, in its own way, is optimal based on pre-defined machining condition such as tool-path pattern, tool-axis control via inclination angles, etc. The proper tool-length should also be provided. The tool-length should be as small as possible in order to enhance machinability as well as surface finish. A feasible tool-length at each NC block can be obtained by checking interference between workpiece and tool components, usually when the tool-axis is not modified at this stage for most CAM systems. Then the minimum feasible tool-length for an NC file consisting of N blocks is the maximum of N tool-length values. However, it can be noted that slight modification of tool-axis at each block may reduce the minimum feasible tool-length in mold & die machining. This approach can effectively be applied in machining feature regions such as steep wall or deep cavity. It has been implemented and is used at a molding die manufacturing company in Korea.

• Journal of Power Electronics
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• v.19 no.6
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• pp.1429-1439
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• 2019

Buck-Boost LLC (BBLLC) converters based on a PWM + phase control strategy are good candidates for high efficiency, high power density and wide input range applications. Nevertheless, they suffer from large computational complexity when it comes to calculating the optimal phase for ZVS of all the switches. In this paper, a method is proposed for a microcontroller unit (MCU) to calculate the optimal phase quickly and accurately. Firstly, a 2-D lookup table of the phase is established with an index of the input voltage and output current. Then, a bilinear interpolation method is applied to improve the accuracy. Meanwhile, simplification of the phase equation is presented to reduce the computational complexity. When compared with conventional curve-fitting and LUT methods, the proposed method makes the best tradeoff among the accuracy of the optimal phase, the computation time and the memory consumption of the MCU. Finally, A 350V-420V input, 24V/30A output experimental prototype is built to verify the proposed method. The efficiency can be improved by 1% when compared with the LUT method, and the computation time can be reduced by 13.5% when compared with the curve-fitting method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2422-2443
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• 2020

This paper studies a single-user Mobile Edge Computing (MEC) system where mobile device (MD) includes an application consisting of multiple computation components or tasks with dependencies. MD can offload part of each computation-intensive latency-sensitive task to the AP integrated with MEC server. In order to accomplish the application faultlessly, we calculate out the optimal task offloading strategy in a time-division manner for a predetermined execution order under the constraints of limited computation and communication resources. The problem is formulated as an optimization problem that can minimize the energy consumption of mobile device while satisfying the constraints of computation tasks and mobile device resources. The optimization problem is equivalently transformed into solving a nonlinear equation with a linear inequality constraint by leveraging the Lagrange Multiplier method. And the proposed dual Bi-Section Search algorithm Bi-JOTD can efficiently solve the nonlinear equation. In the outer Bi-Section Search, the proposed algorithm searches for the optimal Lagrangian multiplier variable between the lower and upper boundaries. The inner Bi-Section Search achieves the Lagrangian multiplier vector corresponding to a given variable receiving from the outer layer. Numerical results demonstrate that the proposed algorithm has significant performance improvement than other baselines. The novel scheme not only reduces the difficulty of problem solving, but also obtains less energy consumption and better performance.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.189-191
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• 1995

This paper proposes a design of self-tuning fuzzy controller based on evolutionary computation. Optimal membership functions are found by using evolutionary computation. Genetic algorithms and evolution strategy are used for tuning of fuzzy membership function. An arbitrarily speed trajectory is selected to show the performance of the proposed methods. Experiment results show the good performance in the DC motor control system with the self-tuning fuzzy controller based on evolutionary computation.

• Journal of Advanced Marine Engineering and Technology
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• v.22 no.2
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• pp.174-180
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• 1998

Robust stability of discrete-time regulators which utilize state predictors to compensate computation delays is considered. Novel expressions for the return difference matrices and the complementary sensitivity matrices at the input and the output of the regulator are found to obtain simple bounds for unstructured perturbations. Robust stability for pertubations of the system matrix and /or the gain matrix is also considered. under certain restriction on the nominal system simple bounds for the pertubations are obtained directly from the characteristic equation. It is shown that as far as the effect of the computation delays concerns these bounds have explicit relation to those for the unstructured pertubations.