• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.1132-1136
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• 2014

In the context of increasing electric energy consumption in a data center, energy efficiency improvement is strongly emphasized. In a data center, electric energy is largely consumed by DC power supply system, which is based on a rectifier composed by multiple parallel converters. Therefore, rectifier efficiency must be improved for minimizing loss of DC power supply system. Rectifier efficiency can be modulated by load allocation to converters because converter efficiency depends on input AC power. In this paper, we propose a new control method to maximize rectifier efficiency. The method can control load allocation to converters by introducing active power converter control scheme and start-and-stop of converters. In order to illustrate optimal load allocations in a rectifier, a maximization problem of rectifier efficiency is formulated as a nonlinear optimization one. The problem is solved by Lagrangian relaxation method and the computation results provide the validity of proposed method.

• International Journal of Quality Innovation
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• v.9 no.2
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• pp.57-77
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• 2008

The $21^{st}$ century is a new century of environmental protection. Environmental protection is one of the most important subject matters yet to come. Moreover, as the public pays more attention to environmental problems, enterprises should increase their investment in environmental management. Therefore, determining the investment level for environmental management and allocating the investment to associated environmental management activities has become a major task. The principal and agent theory and sales response functions are used for analysis in this research. The allocation of capital investment in environmental management is found to have significant impact on the aggregate sales response, aggregate profit and investment level. Therefore, in preparing the budget for environmental management, enterprises should focus on investment allocation decisions, determine the investment level and allocation method using integrated means, and apply submarket data in the allocation decision-making process. In other words, in setting the investment level, executive management should take managers' willingness into consideration. In allocating capital investment, managers should identify the optimal allocation method based on submarket characteristics.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.9
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• pp.1889-1894
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• 2011

Channel allocation is one of the important issues in the multichannel transmission. In the cognitive radio networks, channel allocation scheme should be designed to improve spectrum efficiency without interfering with the transmission of licensed users. In this paper, we propose a spectrum hole prediction based channel allocation scheme. The proposed channel allocation scheme, predicts spectrum hole by using the channel success rate, and limit the transmission of secondary user's data, and it reduces the interference to the primary user. The performance of proposed channel allocation scheme is evaluated by the computer simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.1996-2013
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• 2015

This paper considers a scenario that more D2D users exist in the cell, they compete for cellular resources to increase their own data rates, which may cause transmission interference to cellular users (CU) and the unfairness of resource allocation. We design a resource allocation scheme for selfish D2D users assisted by cooperative relay technique which is used to further enhance the users' transmission rates, meanwhile guarantee the QoS requirement of the CUs. Two transmission modes are considered for D2D users: direct transmission mode and cooperative relay transmission mode, both of which reuses the cellular uplink frequency resources. To ensure the fairness of resource distribution, Nash bargaining theory is used to determine the transmission mode and solve the bandwidth allocation problem for D2D users choosing cooperative relay transmission mode, and coalition formation game theory is used to solve the uplink frequency sharing problem between D2D users and CUs through a new defined "Selfish order". Through theoretical analysis, we obtain the closed Nash bargaining solution under CUs' rate constraints, and prove the stability of the formatted coalition. Simulation results show that the proposed resource allocation approach achieves better performance on resource allocation fairness, with only little sacrifice on the system sum rates.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.11
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• pp.1144-1155
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• 2006

Digital communication networks have become a core technology in advanced building automation systems. BACnet(Building Automation and Control networks) is a standard data communication protocol designed specifically for building automation and control systems. BACnet adopts Master-Slave/Token-Passing(MS/TP) protocol as one of its field level networks. In this study, we introduce a method of implementing a bandwidth allocation scheme in the MS/TP protocol. The bandwidth allocation scheme improves the capability of real-time communication of the original MS/TP protocol. The bandwidth allocation scheme introduced in this paper can be easily implemented in the existing MS/TP protocol with a slight modification. In this study, we actually developed the hardware and firmware of the modified MS/TP communication module in which the bandwidth allocation scheme is implemented. Using the modified MS/TP communication module, we developed an experimental model in order to examine the validity of the bandwidth allocation scheme in the MS/TP protocol. Experimental results show that the modified MS/TP protocol satisfies the requirements of real time communication for periodic and urgent messages of BACnet communication services.

• Journal of Information Processing Systems
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• v.17 no.4
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• pp.721-736
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• 2021

For the mobile edge computing (MEC) system supporting dense network, a joint allocation algorithm of computing and communication resources based on reinforcement learning is proposed. The energy consumption of task execution is defined as the maximum energy consumption of each user's task execution in the system. Considering the constraints of task unloading, power allocation, transmission rate and calculation resource allocation, the problem of joint task unloading and resource allocation is modeled as a problem of maximum task execution energy consumption minimization. As a mixed integer nonlinear programming problem, it is difficult to be directly solve by traditional optimization methods. This paper uses reinforcement learning algorithm to solve this problem. Then, the Markov decision-making process and the theoretical basis of reinforcement learning are introduced to provide a theoretical basis for the algorithm simulation experiment. Based on the algorithm of reinforcement learning and joint allocation of communication resources, the joint optimization of data task unloading and power control strategy is carried out for each terminal device, and the local computing model and task unloading model are built. The simulation results show that the total task computation cost of the proposed algorithm is 5%-10% less than that of the two comparison algorithms under the same task input. At the same time, the total task computation cost of the proposed algorithm is more than 5% less than that of the two new comparison algorithms.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.40
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• pp.169-178
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• 1996

Geographically dispersed computing system is made of computers interconnected by a telecommunications network. To make the system operated efficiently, system designer must determine the allocation of data files to each node. In designing such distributed computing system, the most important issue is the determination of the numbers and the locations where database files are allocated. This is commonly referred to as the file allocation problem (FAP)[3]. The proposed model is a 0/l integer programming problem minimizing the sum of file storage costs and communication(query and update) costs. File allocation problem belongs to the class of NP-Complete problems. Because of the complexity, it is hard to solve. So, this paper presents an efficient heuristic algorithm to solve the file allocation problem using Tabu Search Technique. By comparing the optimal solutions with the heuristic solutions, it is believed that the proposed heuristic algorithm gives good solutions. Through the experimentation of various starting points and tabu restrictions, this paper presents fast and efficient method to solve the file allocation problem in the distributed computing system.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.4
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• pp.396-407
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• 2015

The literature about intelligence assets allocation focused on mainly single or partial assets such as TOD and GSR. Thus, it is limited in application to the actual environment of operating various assets. In addition, field units have generally vulnerabilities because of depending on qualitative analysis. Therefore, we need a methodology to ensure the validity and reliability of intelligence asset allocation. In this study, detection probability was generated using digital geospatial data in MGIS (Military Geographic Information System) and simulation logic of BCTP (Battle Commander Training Programs) in the R.O.K army. Then, the optimal allocation mathematical model applied concept of simultaneous integrated management, which was developed based on the partial set covering model. Also, the proposed GA (Genetic Algorithm) provided superior results compared to the mathematical model. Consequently, this study will support effectively decision making by the commander by offering the best alternatives for optimal allocation within a reasonable time.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.325-329
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• 2007

The mobile and multimedia service on wireless network have been leaded from the improvement of telecommunication techniques. A typical multimedia service, a video transmission usually requires larger bandwidth than voice transmission. Many channel allocation algorithms for Orthogonal Frequency Division Multiple Access (OFBMA) to use resources more efficiently, Previous channel allocation algorithms have developed with an assumption that the data traffic is constant bit rate (CBR). However, existing algorithms are not suitable to video traffic because it usually generates a variable bit rate (VBR) traffic. In this paper, we proposed a new channel allocation algorithm called a queue-based channel allocation. it is more suitable to transmit the video traffics. Also, a problem are notified in case of realtime generated video traffic and a corresponding heuristic solution was proposed.

• ETRI Journal
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• v.34 no.5
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• pp.771-774
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• 2012

Typical channel allocation algorithms for secondary users do not include processes to reduce the frequency of switching from one channel to another caused by random interruptions by primary users, which results in high packet drops and delays. In this letter, with the purpose of decreasing the number of switches made between channels, we propose a nonparametric channel allocation algorithm that uses robust kernel density estimation to effectively schedule idle channel resources. Experiment and simulation results demonstrate that the proposed algorithm outperforms both random and parametric channel allocation algorithms in terms of throughput and packet drops.