• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.5
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• pp.826-832
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• 2015

In wireless networks, it is important to guarantee the energy efficiency and receiver fairness for satisfying service provider and customer at the same time. In this paper, we propose a resource allocation algorithm which improves energy efficiency as well as receiver fairness based on optimization techniques. In the proposed algorithm, subchannel and power are allocated to receivers iteratively in the consideration of channel state information, amount of dissipated power, and receiver rate, in order to improve energy efficiency and receiver fairness. Through simulation, we show the effectiveness and superiority of the proposed algorithm in terms of energy efficiency and receiver fairness.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.8
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• pp.471-480
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• 2003

The design of a measurement system to perform Harmonic State Estimation (HSE) is a very complex problem. Among the reasons for its complexity are the system size, conflicting requirements of estimator accuracy, reliability in the presence of transducer noise and data communication failures, adaptability to change in the network topology and cost minimization. In particular, the number of harmonic instruments available is always limited. Therefore, a systematic procedure is needed to design the optimal placement of measurement points. This paper presents a new HSE algorithm which is based on an optimal placement of measurement points using Genetic Algorithms (GAs) which is widely used in areas such as: optimization of the objective function, learning of neural networks, tuning of fuzzy membership functions, machine learning, system identification and control. This HSE has been applied to the Simulation Test Power System for the validation of the new HSE algorithm. The study results have indicated an economical and effective method for optimal placement of measurement points using Genetic Algorithms (GAs) in the Harmonic State Estimation (HSE).

• ETRI Journal
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• v.27 no.4
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• pp.341-354
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• 2005

The adaptation of video according to the heterogeneous and dynamic resource constraints on networks and devices, as well as on user preferences, is a promising approach for universal access and consumption of video content. For optimal adaptation that satisfies the constraints while maximizing the utility that results from the adapted video, it is necessary to devise a systematic way of selecting an appropriate adaptation operation among multiple feasible choices. This paper presents a general conceptual framework that allows the formulation of various adaptations as constrained optimization problems by modeling the relations among feasible adaptation operations, constraints, and utilities. In particular, we present the feasibility of the framework by applying it to a use case of rate adaptation of MPEG-4 video with an explicit modeling of adaptation employing a combination of frame dropping and discrete cosine transform coefficient dropping, constraint, utility, and their mapping relations. Furthermore, we provide a description tool that describes the adaptation-constraint-utility relations as a functional form referred to as a utility function, which has been accepted as a part of the terminal and network quality of service tool in MPEG-21 Digital Item Adaptation (DIA).

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.120-125
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• 2020

Supply chain managers seek to achieve global optimization by solving problems in the supply chain's business process. However, companies in the supply chain hide the adverse information and inform only the beneficial information, so the information is distorted and cannot be the information that describes the entire supply chain. In this case, supply chain managers can directly collect and analyze supply chain activity data to find and manage the companies described by the data. Therefore, this study proposes a method to collect the order-inventory information from each company in the supply chain and detect the companies whose data characteristics are explained through deep learning. The supply chain consists of Manufacturer, Distributor, Wholesaler, Retailer, and training and testing data uses 600 weeks of time series inventory information. The purpose of the experiment is to improve the detection accuracy by adjusting the parameter values of the deep learning network, and the parameters for comparison are set by learning rate (lr = 0.001, 0.01, 0.1) and batch size (bs = 1, 5). Experimental results show that the detection accuracy is improved by adjusting the values of the parameters, but the values of the parameters depend on data and model characteristics.

• Journal of the Korea Society of Computer and Information
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• v.17 no.12
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• pp.131-136
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• 2012

In these days, with the diffusion of mobile equipments, the number of WiFi Access Point (AP) is increasing, and the growth of WiFi AP causes the throughput degradation due to interferences between APs. This recent phenomenon demands the method able to be utilized with current WiFi network to improve the throughput of Wireless LANs. This paper studied the channel assignment method and several throughput enhancement methods to optimize Radio Resource Management (RRM) for distributed infrastructure WLANs. As a result, it was able to put AP independently, improve older allocation error, and improve execution speed.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.28 no.4
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• pp.501-518
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• 2017

Reducing the time it takes for researchers to acquire knowledge and introduce them into research activities can be regarded as an indispensable factor in improving the productivity of research. The purpose of this research is to cluster the information usage patterns of KOSEN users and to suggest optimization method of personalized recommendation service algorithm for grouped users. Based on user research activities and usage information, after identifying appropriate services and contents, we applied a Spark based big data analysis technology to derive a personal recommendation algorithm. Individual recommendation algorithms can save time to search for user information and can help to find appropriate information.

• Journal of Communications and Networks
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• v.18 no.4
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• pp.610-618
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• 2016

A green cognitive radio network (CRN), characterized by base stations (BSs) that conserve energy during sleep periods, is a promising candidate for realizing more efficient spectrum allocation. To improve the spectrum efficiency and achieve greener communication in wireless applications, we consider CRNs with an long term evolution advanced (LTE-A) structure and propose a novel energy-saving strategy. By establishing a type of preemptive priority queueing model with a single vacation, we capture the stochastic behavior of the proposed strategy. Using the method of matrix geometric solutions, we derive the performance measures in terms of the average latency of secondary user (SU) packets and the energy-saving degree of BSs. Furthermore, we provide numerical results to demonstrate the influence of the sleeping parameter on the system performance. Finally, we compare the Nash equilibrium behavior and social optimization behavior of the proposed strategy to present a pricing policy for SU packets.

• Journal of Communications and Networks
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• v.18 no.4
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• pp.619-628
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• 2016

This paper describes a theoretical framework for rate allocation to maximize the power efficiency of overall heterogeneous wireless networks whose users are assumed to have multihoming capabilities. Therefore, the paper first presents a power consumption model considering the circuit power and radio transmission power of each wireless network. Using this model, two novel power efficient rate allocation schemes (PERAS) for multihoming services are proposed. In this paper, the convex optimization problem for maximizing the power efficiency over wireless networks is formulated and solved while guaranteeing the required quality of service (QoS). Here, both constant bit rate and variable bit rate services are considered. Furthermore, we extend our theoretical framework by considering the sleep-operation management of wireless networks. The performance results obtained from numerical analysis reveal that the two proposed schemes offer superior performance over the existing rate allocation schemes for multihoming services and guarantee the required QoS.

• Journal of information and communication convergence engineering
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• v.17 no.4
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• pp.246-254
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• 2019

This paper proposes a solution to the problem of finding a subgraph for a given instance of many terminals on a Euclidean plane. The subgraph is a tree, whose nodes represent the chosen terminals from the problem instance, and whose edges are line segments that connect two corresponding terminals. The tree is required to have the maximum number of nodes while the length is limited and is not sufficient to interconnect all the given terminals. The problem is shown to be NP-hard, and therefore a genetic algorithm is designed as an efficient practical approach. The method is suitable to various probable applications in layout optimization in areas such as communication network construction, industrial construction, and a variety of machine and electronics design problems. The proposed heuristic can be used as a general-purpose practical solver to reduce industrial costs by determining feasible interconnections among many types of components over different types of physical planes.

• KIEE International Transactions on Power Engineering
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• v.5A no.3
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• pp.228-234
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• 2005

This paper presents the evaluation of reactive power pricing through the control of generator voltages under the assumption that the reactive power market has been transformed into the real power market. By applying the concept of economic dispatch, which minimizes the total cost of real power generation to reactive power generation, the algorithm for implementing reactive power pricing is proposed to determine the optimum voltage profiles of generators. It consists of reactive power voltage equation, the objective function that minimizes the total cost of reactive power generation, and linear analysis of inequality constraints in relation to the load voltages. From this algorithm, the total cost of the reactive power generation can be yielded to the minimum value within network constraints as the range of load voltages. This may provide the fair and reasonable price information for reactive power generation in the deregulated electricity market. The proposed algorithm has been tested on the IEEE 14-bus system using MATLAB.