• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.116.6-116
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• 2002

$\textbullet$ Concept of Adaptive Scaling Factor $\textbullet$ Initial Value and Boundary Conditions $\textbullet$ Adaptive Scaling Factor $\textbullet$ Simulation and Experimental Results

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3584-3602
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• 2022

NFV realizes flexible and rapid software deployment and management of network functions in the cloud network, and provides network services in the form of chained virtual network functions (VNFs). However, using VNFs to provide quality guaranteed services is still a challenge because of the inherent difficulty in intelligently scaling VNFs to handle traffic fluctuations. Most existing works scale VNFs with fixed-capacity instances, that is they take instances of the same size and determine a suitable deployment location without considering the cloud network resource distribution. This paper proposes a traffic forecasted assisted proactive VNF scaling approach, and it adopts the instance capacity adaptive to the node resource. We first model the VNF scaling as integer quadratic programming and then propose a proactive adaptive VNF scaling (PAVS) approach. The approach employs an efficient traffic forecasting method based on LSTM to predict the upcoming traffic demands. With the obtained traffic demands, we design a resource-aware new VNF instance deployment algorithm to scale out under-provisioning VNFs and a redundant VNF instance management mechanism to scale in over-provisioning VNFs. Trace-driven simulation demonstrates that our proposed approach can respond to traffic fluctuation in advance and reduce the total cost significantly.

• ETRI Journal
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• v.33 no.3
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• pp.407-414
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• 2011

In an effort to reduce energy consumption, research into adaptive power management in real-time systems has become widespread. In this paper, a novel dynamic voltage scaling scheme is proposed for multiprocessor systems. Based on the concept of the Nash bargaining solution, a processor's clock speed and supply voltage are dynamically adjusted to satisfy these conflicting performance metrics. In addition, the proposed algorithm is implemented to react adaptively to the current system conditions by using an adaptive online approach. Simulation results clearly indicate that the superior performance of the proposed scheme can strike the appropriate performance balance between contradictory requirements.

• ETRI Journal
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• v.36 no.4
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• pp.591-598
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• 2014

This paper proposes a new min-sum algorithm for low-density parity-check decoding. In this paper, we first define the negative and positive effects of the received signal-to-noise ratio (SNR) in the min-sum decoding algorithm. To improve the performance of error correction by considering the negative and positive effects of the received SNR, the proposed algorithm applies adaptive scaling factors not only to extrinsic information but also to a received log-likelihood ratio. We also propose a combined variable and check node architecture to realize the proposed algorithm with low complexity. The simulation results show that the proposed algorithm achieves up to 0.4 dB coding gain with low complexity compared to existing min-sum-based algorithms.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.105-110
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• 2018

This paper compare the adaptive equalization performance of NM-MMA (Novel Mixed-MMA) algorithm which using the mixed const function by scaling factor values. The mixed cost function of NM-MMA composed of the appropriate weighted addition of gradient vector in the MMA and SE-MMA cost function, and updating the tap coefficient based on these function, it is possible to improve the convergence speed and MSE value of current algorithm. The computer simulation was performed in the same channel, step size, SNR environment by changing the scaling factor, and its performance were compared appling the equalizer output constellation, residual isi, MD, MSE, SER. As a result of computer simulation, the residual values of performance index were reduced in case of the scaling factor of MMA cost function was greater than the scaling factor of SE-MMA. and the convergence speed was improved in case of the scaling factor of SE-MMA was greater than the MMA.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2807-2810
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• 2003

In this paper, we propose a fuzzy control method for improving the control performance by automatically tuning the scaling factor. The proposed method is that automatically tune the input scaling factor and the output scaling factor of fuzzy logic system through neural network. Used neural network is ADALINE (ADAptive Linear NEron) neural network with delayed input. ADALINE neural network has simple construct, superior learning capacity and small computation time. In order to verify the effectiveness of the proposed control method, we performed simulation. The results showed that the proposed control method improves considerably on the environment of the disturbance.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.404-406
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• 1998

In this paper, we propose a scaling factor tuning method to improve the performance of fuzzy controller. Tuning rules and reasoning are utilized on-line to determine the scaling factors based on absolute value of the error and its difference. A adaptive evolutionary computation (AEC) is used to search for the optimal tuning rules that will maximize the fitness function. Finally, the proposed fuzzy controller is applied to the angular stabilization of an inverted pendulum.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.17 no.4
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• pp.279-294
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• 2013

We are interested in an adaptive grid method for hyperbolic equations. A multiresolution analysis, based on a biorthogonal family of interpolating scaling functions and lifted interpolating wavelets, is used to dynamically adapt grid points according to the physical field profile in each time step. Traditional finite-difference schemes with fixed stencils produce high oscillations around sharp discontinuities. In this paper, we hybridize high-resolution schemes, which are suitable for capturing singularities, and apply a finite-difference approach to the scaling functions at non-singular points. We use a total variation diminishing Runge-Kutta method for the time integration. The computational cost is proportional to the number of points present after compression. We provide several numerical examples to verify our approach.

• The Transactions of the Korean Institute of Power Electronics
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• v.17 no.5
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• pp.423-430
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• 2012

An adaptive maximum power point tracking (MPPT) scheme employing a variable scaling factor is presented. A MPPT control loop was constructed analytically and the magnitude variation in the MPPT loop gain according to the operating point of the PV array was identified due to the nonlinear characteristics of the PV array output. To make the crossover frequency of the MPPT loop gain consistent, the variable scaling factor was determined using an approximate curve-fitted polynomial equation about linear expression of the error. Therefore, a desirable dynamic response and the stability of the MPPT scheme were maintained across the entire MPPT voltage range. The simulation and experimental results obtained from a 3 KW rated prototype demonstrated the effectiveness of the proposed MPPT scheme.

• Structural Engineering and Mechanics
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• v.39 no.6
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• pp.767-793
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• 2011

An efficient edge-based smoothed finite element method (ES-FEM) has been recently developed for solving solid mechanics problems. The ES-FEM uses triangular elements that can be generated easily for complicated domains. In this paper, the complexity study of the ES-FEM based on triangular elements is conducted in detail, which confirms the ES-FEM produces higher computational efficiency compared to the FEM. Therefore, the ES-FEM offers an excellent platform for adaptive analysis, and this paper presents an efficient adaptive procedure based on the ES-FEM. A smoothing domain based energy (SDE) error estimate is first devised making use of the features of the ES-FEM. The present error estimate differs from the conventional approaches and evaluates error based on smoothing domains used in the ES-FEM. A local refinement technique based on the Delaunay algorithm is then implemented to achieve high efficiency in the mesh refinement. In this refinement technique, each node is assigned a scaling factor to control the local nodal density, and refinement of the neighborhood of a node is accomplished simply by adjusting its scaling factor. Intensive numerical studies, including an actual engineering problem of an automobile part, show that the proposed adaptive procedure is effective and efficient in producing solutions of desired accuracy.