• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2783-2804
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• 2021

In the network function virtualization environment, dynamic changes in network traffic will lead to the dynamic changes of service function chain resource demand, which entails timely dynamic adjustment of service function chain resource configuration. At present, most researches solve this problem through virtual network function migration and link rerouting, and there exist some problems such as long service interruption time, excessive network operation cost and high penalty. This paper proposes a dynamic adjustment method of service function chain resource configuration for the dynamic changes of network traffic. First, a dynamic adjustment request of service function chain is generated according to the prediction of network traffic. Second, a dynamic adjustment strategy of service function chain resource configuration is determined according to substrate network resources. Finally, the resource configuration of a service function chain is pre-adjusted according to the dynamic adjustment strategy. Virtual network functions combination and virtual machine reusing are fully considered in this process. The experimental results show that this method can reduce the influence of service function chain resource configuration dynamic adjustment on quality of service, reduce network operation cost and improve the revenue of service providers.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.81-84
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• 2007

This paper describes general procedure and results of the GPS 3rd odor network adjustment which has been carried out for determining coordinates sets with respect to new Korean Geodetic Datum, so-call Korean Geodetic Datum 2002 (KGD 2002). The adjustment begins with minimally constrained adjustments with respect to each of the 69 campaign networks. This was followed by constructing and adjusting sixteen block network. After detecting and removing outliers in the observation file, an attempt was made by applying the empirical stochastic modeling techniques used in the 2nd order network adjustment, so as to determine the magnitude of absolute and relative error for the estimated baseline vector from the GPS data processing. The over constrained adjustment were, in sequence, performed against each of the block network. In this adjustment, both of the 2nd order control points in the block network and the 3rd order control points overlapped with adjacent network whose coordinates were already determined from a preceding adjustment. The final adjustment results have shown that the accuracy of the 3rd order network adjustment was better than 1cm and 2cm in horizontal and vertical component, respectively.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.4
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• pp.367-380
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• 2011

This paper has focused on deriving a GPS based geodetic network adjustment strategy to continuously determine coordinate sets of the national geodetic control points. After domestic literature review on the topic and overseas case studies about countries that recently reformed their geodetic infrastructure have been carried out, a simplified geodetic network consisting of two layers, namely GPS active and passive network, has been proposed to maximize effectiveness of the network adjustment through reducing the number of the passive points. Furthermore, a GPS data processing and network adjustment procedure has been derived to support the continuous management scheme. While a scheme for the active layer adopts a sequential least squares adjustment based on a multi-baseline, that of the passive layer employs a multi-session adjustment technique with respect to 3-dimensional baseline vectors. Finally, experimental adjustment against a network comprising 24 active and 6,900 passive stations has been performed to demonstrate the efficiency and the effectiveness of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.4
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• pp.448-457
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• 1998

A neural network based control algorithm with fuzzy compensation is proposed for the automated adjustment in the production of electronic end-products. The process of adjustment is to tune the variable devices in order to examine the specified performances of the products ready prior to packing. Camcorder is considered as a target product. The required test and adjustment system is developed. The adjustment system consists of a NNC(neural network controller), a sub-NNC, and an auxiliary algorithm utilizing the fuzzy logic. The neural network is trained by means of errors between the outputs of the real system and the network, as well as on the errors between the changing rate of the outputs. Control algorithm is derived to speed up the learning dynamics and to avoid the local minima at higher energy level, and is able to converge to the global minimum at lower energy level. Many unexpected problems in the application of the real system are resolved by the auxiliary algorithms. As the adjustments of multiple items are related to each other, but the significant effect of performance by any specific item is not observed. The experimental result shows that the proposed method performs very effectively and are advantageous in simple architecture, extracting easily the training data without expertise, adapting to the unstable system that the input-output properties of each products are slightly different, with a wide application to other similar adjustment processes.

• Journal of the Korean Geophysical Society
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• v.6 no.1
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• pp.1-11
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• 2003

There are numerous adjustment techniques that deal with the adjustment of geodetic networks but the least squares adjustment is the most common one. During the network adjustment procedure two techniques can be used, the free network adjustment technique and the constrained network adjustment technique. In order to determine the optimum technique for adjusting the geodetic networks, which used for the geodynamical purposes, data from two different geodetic networks "Sinai geodetic network, Egypt, and HGN network, South Korea" had been examined. The used networks had a different configuration and located in different areas with different seismic activity. The results show that both techniques have a high accuracy and no remarkable differences in terms of RMS. On the contrary, the resulted coordinates shows that the constrained network adjustment technique not only cause a remarkable distortion in the station final coordinates but also if the fixed points that define the datum parameters are changed different solutions for the coordinates will be determined. This distortion affect not only in the determination of point displacement but also in the estimation of the deformation parameters, which play a significant role in the geodynamical interpretation of results. Comparing the results which obtained from both techniques with the widely known geodynamical models of the area reviles that the free network adjustment technique results are clearly match with these models, while those obtained from the constrained technique didn’t match at all. By considering the results it seams to be that the free network adjustment technique is the optimum technique, which can be used for the geodetic network adjustment.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.2
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• pp.103-110
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• 2015

This paper planned for the adjustment of unified control points by compared adjusted software for integrated network and the national integrated network. There may be some errors in the survey date and interpretation of data processing due to applying different software each year. To minimize errors, we performed a precision network adjustment by consolidating control points per observation session over years. Prior to perform the integrated network adjustment with the GPS analysis program (GLOBK) for the final integrated network adjustment, the Quasi-Observation Combination Analysis(QOCA), the Global Kalman filter VLBI and the GLOBK were compared and analyzed to perform an integrated network adjustment. The integrated network adjustment result indicates that the RMSE was rather big with ±0.03m along the vertical axis, but ±0.006m along the horizontal, that is not much different from the existing result.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.65-69
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• 1992

In this paper, an implementation of neuro-controller with an application of artificial neural network for an adjustment and tuning process for the completed electronics devices is presented. Multi-layer neural network model is employed with the learning method of error back-propagation. For the intelligent control of adjustment and tuning process, the neural network emulator (NNE) and the neural network controller(NNC) are developed. Computer simulation reveals that the intelligent controllers designed can function very effectively as tools for computer aided adjustment system. The applications of the controllers to the real systems are also demonstrated.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.13 no.1
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• pp.107-113
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• 1995

Generally, the objectives of the geodetic network adjustments are for solving the configuration of geodetic net-works and the problem of observation plans. In this study, assuming that the configuration is fixed, for improving the accuracy of geodetic networks, we focus on choosing adjustment control points and adjustment methods. By choosing adjustment control points and adjustment methods, the adjustment result accuracy of national geodetic networks can be different. So, in this study, we introduce the algorithm that use free network adjustment concept to minimize the displacements of new station points but fixing existing control points. Then, us-ing adjustment results, we can check the errors of existing control points. After checking the errors of existing control point, in case of severe error points in existing control points, we change those points into unknown station points and repeat the algorithm to optimize the coordinates of new station points. As applying this algorithm to simulation network, we can check the errors of existing control points. And changing severe error points into unknown station points, we can decrease the errors of network and optimize the coordinates of new station points. From the results of simulation network adjustment, we think that, as applying this algorithms to sequential adjustment of geodetic network and public surveying that using national geodetic network, the accuracy of network adjustments can be improved.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.1
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• pp.79-89
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• 1993

This paper deals with a computer aided control of an adjustment process for the complete electronic devices by means of an application of artificial neural network and an implementation of neuro-controller for intelligent control. Multi-layer neural network model is employed as artificial neural network with the learning method of the error back propagation. Information initially available from real plant under control are the initial values of plant output, and the augmented plant input and its corresponding plant output at that time. For the intelligent control of adjustment process utilizing artificial neural network, the neural network emulator (NNE) and the neural network controller(NNC) are developed. The initial weights of each neural network are determined through off line learning for the given product and it is also employed to cope with environments of the another product by on line learning. Computer simulation, as well as the application to the real situation of proposed intelligent control system is investigated.

• Journal of Korean Society of Transportation
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• v.10 no.2
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• pp.25-42
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• 1992

The purpose of this paper is to construct a model to compute a progression adjustment factor on a signalized network. In a way to construct the model, a simulation method is introduced and the TRAF-NETSIM is used as a tool of simulation. The structure of the network chooses an urban arterial network so as to measure the effect of progression and compute average stopped delay on each link. A regression model is constructed by using the results of the simulation. The stepwise variable selection in the regression model in used. The findings of this paper are as follows: i)The secondary queue and platoon ratio are sensitive to the values of the progression adjustment factor ii) The continuous model can practically reflect on various situations in the real world. The platoon adjustment factor can be computed by this model and the data required for this model can be easily obtained in the field.