• Journal of KIISE:Information Networking
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• v.36 no.3
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• pp.212-221
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• 2009

This paper proposes a novel centralized clustering algorithm, "RLCA : Relative Location based Clustering Algorithm for Wireless Sensor Networks," for constructing geographically well-distributed clusters in general WSNs. RLCA does not use GPS and controls selection-rate of cluster-head based on distances between sensors and BS. We empirically show that RLCA's energy efficiency is higher than LEACH's.

• Journal of Electrical Engineering and Technology
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• v.5 no.3
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• pp.353-362
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• 2010

This paper presents a centralized control algorithm for power system performance in the Korean power system using Flexible AC Transmission Systems (FACTS) devices. The algorithm is applied to the Korean power system throughout the metropolitan area in order to alleviate inherent stability problems, especially concerns with voltage stability. Generally, control strategies are divided into local and centralized control. This paper is concerned with a centralized control strategy in terms of the global system. In this research, input data of the proposed algorithm and network data are obtained from the SCADA/EMS system. Using the full system model, the centralized controller monitors the system condition and decides the operating point according to the control objectives that are, in turn, dependent on system conditions. To overcome voltage collapse problems, load-shedding is currently applied in the Korean power system. In this study, the application of the coordination between FACTS and switch capacitor (SC) can restore the solvability without load shedding or guarantee the FV margin when the margin is insufficient. Optimal Power Flow (OPF) algorithm, for which the objective function is loss minimization, is used in a stable case. The results illustrate examples of the proposed algorithm using SCADA/EMS data of the Korean power system in 2007.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.4
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• pp.87-104
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• 2014

This paper proposes regionally centralized multistage reverse logistics (cmRL) networks and regionally decentralized multistage reverse logistics (dmRL) networks. cmRL considers whole area of RL network, while dmRL regionally distributed area of RL network. Each type is formulated by the mixed integer programming (MIP) models, which are realized in genetic algorithm (GA) approach. Two types of numerical experiments using RL network are presented and various measures of performance are used for comparing the efficiency of the cmRL and the dmRL. Finally, it is proved that the performance of the cmRL is superior to that of the dmRL.

• Smart Structures and Systems
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• v.11 no.2
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• pp.163-183
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• 2013

Control systems have been greatly studied in recent years and can be classified as: passive, active, semi-active or hybrid systems. Most forms of control systems have been applied in a centralized manner where all the information is sent to a central node where control the algorithm is then calculated. One of the possible problems of centralized control is the difficulty to scale its application. In this paper, a completely decentralized control algorithm is analytically implemented. The algorithm considers that each of the control systems makes the best decision based solely on the information collected at its location. Semi-active control is used in preference to active control because it has minimal energy consumption, little to no possibility of destabilization, a reduction in the possibility of data saturation, and a reduction in the response time in comparison to centralized control.

• Journal of Information Processing Systems
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• v.19 no.1
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• pp.17-32
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• 2023

Centralized hierarchical routing protocols are often used to solve the problems of uneven energy consumption and short network life in wireless sensor networks (WSNs). Clustering and cluster head election have become the focuses of WSNs. In this paper, an energy balanced clustering routing algorithm optimized by sine cosine algorithm (SCA) is proposed. Firstly, optimal cluster head number per round is determined according to surviving node, and the candidate cluster head set is formed by selecting high-energy node. Secondly, a random population with a certain scale is constructed to represent a group of cluster head selection scheme, and fitness function is designed according to inter-cluster distance. Thirdly, the SCA algorithm is improved by using monotone decreasing convex function, and then a certain number of iterations are carried out to select a group of individuals with the minimum fitness function value. From simulation experiments, the process from the first death node to 80% only needs about 30 rounds. This improved algorithm balances the energy consumption among nodes and avoids premature death of some nodes. And it greatly improves the energy utilization and extends the effective life of the whole network.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.5
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• pp.367-377
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• 2019

As an alternative navigation system for the non-GNSS (Global Navigation Satellite System) environment, a new type of DBRN (DataBase Referenced Navigation) which applies both gravity gradient and terrain, and combines filter-based algorithm with profile matching was suggested. To improve the stability of the performance compared to the previous study, both centralized and decentralized EKF (Extended Kalman Filter) were constructed based on gravity gradient and terrain data, and one of filters was selected in a timely manner. Then, the final position of a moving vehicle was determined by combining a position from the filter with the one from a profile matching. In the simulation test, it was found that the overall performance was improved to the 19.957m by combining centralized and decentralized EKF compared to the centralized EKF that of 20.779m. Especially, the divergence of centralized EKF in two trajectories located in the plain area disappeared. In addition, the average horizontal error decreased to the 16.704m by re-determining the final position using both filter-based and profile matching solutions. Of course, not all trajectories generated improved performance but there is not a large difference in terms of their horizontal errors. Among nine trajectories, eights show smaller than 20m and only one has 21.654m error. Thus, it would be concluded that the endemic problem of performance inconsistency in the single geophysical DB or algorithm-based DBRN was resolved because the combination of geophysical data and algorithms determined the position with a consistent level of error.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.2
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• pp.8-18
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• 2020

An Exponential Bandwidth Harmony Search with Centralized Global Search (EBHS-CGS) was developed to enhance the performance of a Harmony Search (HS). EBHS-CGS added two methods to improve the performance of HS. The first method is an improvement of bandwidth (bw) that enhances the local search. This method replaces the existing bw with an exponential bw and reduces the bw value as the iteration proceeds. This form of bw allows for an accurate local search, which enables the algorithm to obtain more accurate values. The second method is to reduce the search range for an efficient global search. This method reduces the search space by considering the best decision variable in Harmony Memory (HM). This process is carried out separately from the global search of the HS by the new parameter, Centralized Global Search Rate (CGSR). The reduced search space enables an effective global search, which improves the performance of the algorithm. The proposed algorithm was applied to a representative optimization problem (math and engineering), and the results of the application were compared with the HS and better Improved Harmony Search (IHS).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.9A
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• pp.1405-1412
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• 2000

In this paper, we propose an efficient dynamic wavelength assignment algorithm in distributed WDM (Wavelength-Division Multiplexing) networks without wavelength conversion. The algorithm tries to assign a locally-most-used wavelength distributedly on a fixed routing path. We first formulate our algorithm by using the concept of a sample space which consists of optical fibers connected to nodes on a routing path of a lightpath to be assigned a wavelength. In particular, we analyze the blocking performance mathematically as compared with that of the most-used (MU) wavelength assignment algorithm previously proposed for WDM networks under centralized control. We also obtain numerical results by simulation on the blocking performance of other centralized/distributed wavelength assignment algorithms as well as our algorithm using the M/M/c/c dynamic traffic model. Consequently, we show that analytical results match simulation results and that our algorithm is efficient in distributed WDM networks in terms of blocking performance, control traffic overhead and computation complexity.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.24 no.2
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• pp.1-10
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• 2016

A GPS/SDINS/ST(Star Tracker) integrated sensor algorithm is more robust than the GPS/SDINS and the ST/SDINS systems on exploration of other planets. Most of the advanced studies shown that GPS/SDINS/ST integrated sensor with centralized Kalman filter was more accurate than those 2 integrated systems. The system, however, consist of a single filter, it is vulnerable to defects on failed data. To improve the problem, we work out a study using federated Kalman filter(No-Reset mode) and centralized Kalman filter with adaptive measurement fusion which known as robustness on fault. The simulation results show that the debasing influences are reduced and the computation is enable at least 100Hz. Further researches that the initial calibration in accordance with observability and applying the exploration trajectory are needed.

• International Journal of Control, Automation, and Systems
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• v.4 no.2
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• pp.165-171
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• 2006

This paper proposes a data fusion algorithm of nonlinear multi sensor dynamic systems of synchronous sampling based on filtering step by step. Firstly, the object state variable at the next time index can be predicted by the previous global information with the systems, then the predicted estimation can be updated in turn by use of the extended Kalman filter when all of the observations aiming at the target state variable arrive. Finally a fusion estimation of the object state variable is obtained based on the system global information. Synchronously, we formulate the new algorithm and compare its performances with those of the traditional nonlinear centralized and distributed data fusion algorithms by the indexes that include the computational complexity, data communicational burden, time delay and estimation accuracy, etc.. These compared results indicate that the performance from the new algorithm is superior to the performances from the two traditional nonlinear data fusion algorithms.