• Journal of KIISE:Computing Practices and Letters
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• v.16 no.11
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• pp.1086-1090
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• 2010

In recent, as many applications of sensor networks increase, various techniques have been studied to efficiently operate network systems. The query optimization scheme that is one of such techniques has been studied to reduce the data transmission cost. The data transmission is of great importance to the energy consumption of sensor networks. In this paper, we propose an energy-efficient multiple queries processing scheme by sharing sensor readings for multiple queries, when they are occurred in sensor networks. The proposed scheme reduces unnecessary data transmissions among the sensor nodes by intuitively identifying their locations using the grid structure. It also efficiently shares the data by recognizing the redundant regions of sensor nodes. In order to show the superiority of the proposed scheme, we compare it with the existing scheme in various experiments. As the result, the proposed scheme reduces about 65% energy consumption over the existing scheme.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.433-440
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• 2014

In this study, a method for the low-carbon active distribution system (ADS) planning is proposed. It takes into account the impacts of both network capacity and demand correlation to the renewable energy accommodation, and incorporates demand response (DR) as an available resource in the ADS planning. The problem is formulated as a mixed integer nonlinear programming model, whereby the optimal allocation of renewable energy sources and the design of DR contract (i.e. payment incentives and default penalties) are determined simultaneously, in order to achieve the minimization of total cost and $CO_2$ emissions subjected to the system constraints. The uncertainties that involved are also considered by using the scenario synthesis method with the improved Taguchi's orthogonal array testing for reducing information redundancy. A novel cuckoo search (CS) is applied for the planning optimization. The case study results confirm the effectiveness and superiority of the proposed method.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.9
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• pp.82-87
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• 2008

Faster, safer and cheaper mailing of the postal matter is essential for surviving in the competitive market of home-delivery service. In the past, the domestic delivery business has been nu by only a few number of companies. But more and more number of companies including medium size ones are participating in the business, and the competition is getting severe. This paper proposes a method to select the optimal location of mail distribution centers that minimally connect the local mail centers of some major cities in Korea using the Steiner Tree theory, which is about connecting a finite number of points with a minimal length of paths and has been used in the distribution system optimization and optimal routing of the transmission lines of the electric power system. By using Steiner Tree theory in finding the best location of the postal delivery hub, we may expect the reduction of transportation cost and the increase of profit, resulting in acquiring the superior position in the competitive delivery business. It is expected that we may use the Steiner Tree theory in finding the best location of the electric power substation for the nott higher EHV(extreme high voltage) transmission network.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.1
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• pp.83-90
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• 2015

This paper proposes a Tabu search algorithm to maximize the connectivity between the router nodes and the client nodes in wireless mesh networks. As the number of the router nodes and the client nodes in the networks increases, the amount of calculation for finding the solution would be too much increased. To obtain the optimal solution within a reasonable computation time for a high-density network, we propose a Tabu search algorithm to obtain the optimal solution for maximizing the connectivity. In order to make a search more efficient, we propose some efficient neighborhood generating operations of the Tabu search algorithm. We evaluate those performances through some experiments in terms of the maximum number of the connectivity and the execution time of the proposed algorithm. The comparison results show that the proposed algorithm outperforms other existing algorithms.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.3
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• pp.55-70
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• 2016

The most critical research issue in MANET environment is on supporting reliable communication between various devices. Various Multi-Hop Routing Protocol studies have proceeded. However, some problems you might have found when you use the existing link state routing technique are that it increases Control Message Overhead and it is unstable when node moves in CR circumstance which has transformation of using channel and MIMC circumstance which uses a number of interfaces. This essay offers a technique which is based on On-Demand Hello and the other technique which used Broadcast Interface of optimization as a solution to decrease Control Message Overhead. Also it proposes Quick Route Restoration technique which is utilized by GPS and MPR Selection technique which consider mobility as a solution of stable communication when node moves. Those offered Routing Protocol and OPNET based simulator result will be expected to be an excellent comparison in related research fields.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.843-845
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• 2003

Shortest Path Problems are among the most studied network flow optimization problems, with interesting applications in various fields. One such field is the route determination service, where various kinds of shortest path problems need to be solved in location-based service. Our research aim is to propose a route technique in real-time locationbased service (LBS) environments according to user’s route preferences such as shortest, fastest, easiest and so on. Turn costs modeling and computation are important procedures in route planning. There are major two kinds of cost parameters in route planning. One is static cost parameter which can be pre-computed such as distance and number of traffic-lane. The other is dynamic cost parameter which can be computed in run-time such as number of turns and risk of congestion. In this paper, we propose a new cost modeling method for turn costs which are traditionally attached to edges in a graph. Our proposed route determination technique also has an advantage that can provide service interoperability by implementing XML web service for the OpenLS route determination service specification. In addition to, describing the details of our shortest path algorithms, we present a location-based service system by using proposed routing algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4661-4680
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• 2016

Cognitive radio (CR) technology is an effective solution to the spectrum scarcity issue. Collaborative spectrum sensing is known as a promising technique to improve the performance of spectrum sensing in cognitive radio networks (CRNs). However, collaborative spectrum sensing is vulnerable to spectrum data falsification (SSDF) attack, where malicious users (MUs) may send false sensing data to mislead other secondary users (SUs) to make an incorrect decision about primary user (PUs) activity, which is one of the key adversaries to the performance of CRNs. In this paper, we propose a coalition based malicious users detection (CMD) algorithm to detect the malicious user in CRNs. The proposed CMD algorithm can efficiently detect MUs base on the Geary'C theory and be modeled as a coalition formation game. Specifically, SSDF attack is one of the key issues to affect the resource allocation process. Focusing on the security issues, in this paper, we analyze the power allocation problem with MUs, and propose MUs detection based power allocation (MPA) algorithm. The MPA algorithm is divided into two steps: the MUs detection step and the optimal power allocation step. Firstly, in the MUs detection step, by the CMD algorithm we can obtain the MUs detection probability and the energy consumption of MUs detection. Secondly, in the optimal power allocation step, we use the Lagrange dual decomposition method to obtain the optimal transmission power of each SU and achieve the maximum utility of the whole CRN. Numerical simulation results show that the proposed CMD and MPA scheme can achieve a considerable performance improvement in MUs detection and power allocation.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1243-1258
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• 2017

A new medical materials scheduling system and its modeling method for the complex rescue are presented. Different from other similar system, first both the BeiDou Satellite Communication System (BSCS) and the Special Fiber-optic Communication Network (SFCN) are used to collect the rescue requirements and the location information of disaster areas. Then all these messages will be displayed in a special medical software terminal. After that the bipartite graph models are utilized to compute the optimal scheduling of medical materials. Finally, all these results will be transmitted back by the BSCS and the SFCN again to implement a fast guidance of medical rescue. The sole drug scheduling issue, the multiple drugs scheduling issue, and the backup-scheme selection issue are all utilized: the Kuhn-Munkres algorithm is used to realize the optimal matching of sole drug scheduling issue, the spectral clustering-based method is employed to calculate the optimal distribution of multiple drugs scheduling issue, and the similarity metric of neighboring matrix is utilized to realize the estimation of backup-scheme selection issue of medical materials. Many simulation analysis experiments and applications have proved the correctness of proposed technique and system.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.735-740
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• 2012

In this paper, we introduce design methodologies of polynomial radial basis function neural network classifier with the aid of Principal Component Analysis(PCA) and Linear Discriminant Analysis(LDA). By minimizing the information loss of given data, Feature data is obtained through preprocessing of PCA and LDA and then this data is used as input data of RBFNNs. The hidden layer of RBFNNs is built up by Fuzzy C-Mean(FCM) clustering algorithm instead of receptive fields and linear polynomial function is used as connection weights between hidden and output layer. In order to design optimized classifier, the structural and parametric values such as the number of eigenvectors of PCA and LDA, and fuzzification coefficient of FCM algorithm are optimized by Artificial Bee Colony(ABC) optimization algorithm. The proposed classifier is applied to some machine learning datasets and its result is compared with some other classifiers.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.5
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• pp.537-543
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• 2006

There have been many recent studies on the nonlinear rainfall-runoff modeling, where the use of neural networks is shown to be quite successful. Due to fundamental limitation of linear structures, employing linear models has often been considered inferior to the neural network approaches in this area. However, we believe that with an appropriate extension, the concept of linear impulse responses can be a viable tool since it enables us to understand underlying dynamics principles better. In this paper, we propose the use of multiple impulse responses for the problem of rainfall-runoff analysis. The proposed method is based on a simple and fixed strategy for switching among multiple linear impulse-response models, each of which satisfies the constraints of non-negativity and uni-modality. The computational analysis performed for a certain Korean hydrometeorologic data set showed that the proposed method can yield very meaningful results.