• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권10호
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• pp.4848-4863
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• 2016

The explosive wireless data service requirement accompanied with carbon dioxide emission and consumption of traditional energy has put pressure on both industria and academia. Wireless networks powered with the uneven and intermittent generated renewable energy have been widely researched and lead to a new research paradigm called green communication. In this paper, we comprehensively consider the total generated renewable energy, QoS requirement and channel quality, then propose a utility based renewable energy allocation policy. The utility here means the satisfaction degree of users with a certain amount allocated renewable energy. The energy allocation problem is formulated as a constraint optimization problem and a heuristic algorithm with low complexity is derived to solve the raised problem. Numerical results show that the renewable energy allocation policy is applicable not only to soft QoS, but also to hard QoS and best effort QoS. When the renewable energy is very scarce, only users with good channel quality can achieve allocated energy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권1호
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• pp.216-239
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• 2021

The present work addresses the challenging problem of coordinating power allocation with interference management in multi-robot networks by applying the promising expansion capabilities of multiple-input multiple-output (MIMO) and full duplex systems, which achieves it for maximizing the throughput of networks under the impacts of Doppler frequency shifts and external jamming. The proposed power allocation with interference coordination formulation accounts for three types of the interference, including cross-tier, co-tier, and mixed-tier interference signals with cluster head nodes operating in different full-duplex modes, and their signal-to-noise-ratios are respectively derived under the impacts of Doppler frequency shifts and external jamming. In addition, various optimization algorithms, including two centralized iterative optimization algorithms and three decentralized optimization algorithms, are applied for solving the complex and non-convex combinatorial optimization problem associated with the power allocation and interference coordination. Simulation results demonstrate that the overall network throughput increases gradually to some degree with increasing numbers of MIMO antennas. In addition, increasing the number of clusters to a certain extent increases the overall network throughput, although internal interference becomes a severe problem for further increases in the number of clusters. Accordingly, applications of multi-robot networks require that a balance should be preserved between robot deployment density and communication capacity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권6호
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• pp.1379-1397
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• 2013

We consider a system where a licensed radio spectrum is shared by multiple primary users(PUs) and secondary users(SUs). As the spectrum of interest is licensed to primary network, power and channel allocation must be carried out within the cognitive radio network so that no excessive interference is caused to PUs. For this system, we study the joint beamforming and power allocation problem via game theory in this paper. The problem is formulated as a non-cooperative beamforming and power allocation game, subject to the interference constraints of PUs as well as the peak transmission power constraints of SUs. We design a joint beamforming and power allocation algorithm for maximizing the total throughput of SUs, which is implemented by alternating iteration of minimum mean square error based decision feedback beamforming and a best response based iterative power allocation algorithm. Simulation results show that the algorithm has better performance than an existing algorithm and can converge to a locally optimal sum utility.

• 정보처리학회논문지C
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• 제18C권2호
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• pp.97-102
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• 2011

게임 이론은 다수의 사용자에게 공유 자원을 효율적이고 공정하게 분배할 수 있는 이론적 기반을 제공하므로 이를 대역폭 할당에 이용하려는 연구가 활발히 진행되어 왔다. 그러나 게임 이론에 의한 대역폭 할당 기법들은 적용한 게임 기법들에 따라 동일 조건에서 할당하는 대역폭이 달라진다. 그러나 현재까지 네트워크 분야에서는 게임 이론의 수학적 근거만을 차용하고 있으며 이들이 대역폭 할당 문제에 적용될 때 각 기법 별 특성에 대한 정량적 비교 분석은 이루어지고 있지 않다. 이에 따라 본 논문에서는 다수의 노드가 대역폭을 공유하는 경우 파산(Bankruptcy) 게임 이론과 협상(Bargaining) 게임 이론을 이용하여 송신 노드의 입력율에 따른 각 노드 별 대역폭 할당 기법들의 특성을 비교 분석하고 이에 따른 향후 연구 방향을 제시한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권6호
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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.

• Industrial Engineering and Management Systems
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• 제14권1호
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• pp.11-21
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• 2015

The purpose of this research is to develop algorithms using the Differential Evolution Algorithm (DE) to solve a multi-objective, sources and stages location-allocation problem. The development process starts from the design of a standard DE, then modifies the recombination process of the DE in order improve the efficiency of the standard DE. The modified algorithm is called modified DE. The proposed algorithms have been tested with one real case study (large size problem) and 2 randomly selected data sets (small and medium size problems). The computational results show that the modified DE gives better solutions and uses less computational time than the standard DE. The proposed heuristics can find solutions 0 to 3.56% different from the optimal solution in small test instances, while differences are 1.4-3.5% higher than that of the lower bound generated by optimization software in medium and large test instances, while using more than 99% less computational time than the optimization software.

• 대한안전경영과학회지
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• 제12권1호
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• pp.97-104
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• 2010

Expanded muti-source Weber problem (EWP), which introduced in this paper, is a reverse logistics network design problem to minimize the total transportation cost from customers thorough regional center to central center. Decision factor of EWP are the locations of regional centers and a central center. We introduce a GRASP heuristics for the EWP. In the suggested GRASP, an expanded iterative location allocation method (EILA) is introduced based on the Cooper's iterative location allocation method[3]. For the initial solution of GRASP, allocation first seed (AFSeed) and location first seed (LFSeed) are developed. The computational experiment for the objective value shows that the LFSeed is better than the AFSeed. Also the calculating time of the LFSeed is better than that of the AFSeed.

• International Journal of Reliability and Applications
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• 제12권2호
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• pp.79-94
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• 2011

Redundancy-reliability allocation problems in multi-stage series-parallel systems are addressed in this study. Fuzzy programming techniques are proposed for finding satisfactory solutions. First, a multi-objective programming model is formulated for simultaneously maximizing system reliability and minimizing system total cost. Due to the nature of uncertainty in the problem, the fuzzy set theory and technique are used to convert the deterministic multi-objective programming model into a fuzzy nonlinear programming problem. A heuristic method is developed to get satisfactory solutions for the fuzzy nonlinear programming problem. A Pareto optimal solution is found with maximal degree of satisfaction from the interception area of fuzzy sets. A case study that is related to the electronic control unit installed on aircraft engine over-speed protection system is used to implement the developed approach. Results suggest that the developed fuzzy multi-objective programming model can effectively resolve the fuzzy and uncertain problem when design goals and constraints are not clearly confirmed at the initial conceptual design phase.

• 보건행정학회지
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• 제10권4호
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• pp.99-115
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• 2000

This study was conducted to get a resonable set of budget allocation to public health programs. Matrix Delphi technique was used to obtain the logic of study results and eventually to form a human model which could predict opinion of professionals on budget allocation. Thirty-two professionals in academic and governmental area responded to Delphi survey. Questionnaire was developed using matrix formation, and the matrix was formed by 6 decision criteria on budget allocation and 26 public health programs. The decision criteria are as following: size of problem(morbidity), severity of problem, social equity, importance of prevention, technical feasibility and efficiency of programs. Severity of problem dropped out of the model because it had significant correlation with the size of problem. A total score of each program was obtained by weighting the relative importance of each criteria which also were given by survey respondents. These total scores indicate that the most important public health program is vaccination for infants and children in terms of budget allocation. Monitoring communicable diseases, mental health program, and anti-smoking program are the next. In addition, respondents were asked of the desirable budget size of each program. The result was rearranged by multiple regression model using the scores of each decision criteria. In this process, the current budget size of central government was provided to the respondents, and included in the model. h set of desirable budgets modified using tile model was obtained. Considering the current size of budget, tile results of the model is very different from that of the total score. Managing dementia is ranked the first. Health promotion program for the elderly, rehabilitation of the disabled and monitoring communicable diseases are the next. The need to increase the budget of vaccination for the infants and children was not found as so high. The matrix structure in Delphi survey gave us the precise basis to make optimal decision, and made it possible to develop an opinion predicting model. However the plentifulness and diversity of professional opinions were not fully obtained due to the limited number of decision criteria.

• 한국통신학회논문지
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• 제23권8호
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• pp.2032-2041
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• 1998

비트할당 문제는 영상을 손실 부호화 하는데 있어서 가장 기본적인 것으로, 최대 허용 비트량을 초과하지 않으면서도 복원 영상의 발생 왜곡정도를 최소화 하는 것올 목적으로 하는 것이다. 이러한 비트할당 문제의 최적해를 구하는데 있어서 기존의 최적 비트할당 방법들은 동적 프로그래밍(dynamic programming) 방식에 근간하기 때문에 영상의 수가 증가하거나 움직임 보상을 이용하는 동영상 부호화의 정우에는 해를 구하기 위해서는, 그 방식이 요구하는 계산량과 메포리양이 너무 많아 최적해를 구하는데 있어서 그 한계가 있다. 본 논문에서는 기존의 최적 비트할당 방법들이 지니는 문제점들을 해결하기 위하여 '버트할당 문제의 분할' 과 '2단계 최적화 방법'을 이용하여 기존의 최적 비트할당 방법들에 비해 적은 계산량과 메모리를 요구하면서도 최적 비트할당 결과를 얻을 수 있는 방법 을 제안한다. 또한 제안한 방식을 효과적으로 근사화 할 수 있는 방법에 대해서도 제안한다. 최적 비트할당 결과는 영상 부호화 시스템의 분석, 복원화질의 최고치 파악, 효과적인 근사화 방법의 개발등에 효과적으로 이용될 수 있다. 따라서 본 논문에서 제안하는 방법은 비트할당에 관련된 분야에 효과적으로 이용될 수 있으리라 기대된다.