• 한국공작기계학회논문집
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• 제12권3호
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• pp.31-37
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• 2003

With the paradigm shifting from the principal of manufacturing efficiency to business globalism and rapid adaptation to its environments, more and more enterprises are being virtually organized as manufacturing network of different units in web. The formation of these enterprise called as Virtual Enterprise(VE) is becoming a growing trend as enterprises concentrating on core competence and economic benefit. 13us paper proposes multi-agent based task assignment system for VE, which attempts to address the selection of individually managed partners and the task assignment to them A case example is presented to illustrate how the proposed system can assign the task to partners.

• 한국정보과학회논문지:시스템및이론
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• 제27권3호
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• pp.264-276
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• 2000

최근 인터넷 환경에서의 기술 향상으로 인하여 다양한 정보를 공유하고, 네트워크로 연결된 여러 시스템 자원을 이용하는 것이 용이하게 되었다. 특히, 자바의 애플릿(applet)을 이용한 코드 이동(code migration) 기술은 인터넷의 웹 환경에서 프로그램의 분산을 용이하게 하며, 그 애플릿을 수행하는 브라우저는 이동된 코드의 신뢰성을 보장해준다. 본 논문은 웹 환경에서 이동 가능 코드를 분산시키고, 대량의 연산수행을 지닌 작업을 분배하여 병렬적으로 수행시킨 뒤, 그 결과를 취합하는 웹 기반 병렬 시스템의 설계 및 구현에 관하여 기술한다. 또한, 이 시스템에 참여하는 이질적인 다수의 호스트들은 인터넷이라는 환경에서 지리적으로 떨어져 연결되어 있으므로 성능의 차이 및 가변성을 예상하기 힘들다. 그러므로, 그들 간의 성능 차이를 고려한 태스크 할당 알고리즘 및 심각한 가변성에 대한 적응력이 요구된다. 이 논문에서는 시스템의 구현에 사용될 적응성 향상 기법을 제시하고, 시스템의 작업 처리 성능 및 제안하는 알고리즘들의 효율을 나타내는 성능 평가 결과를 제시한다.

• 정보처리학회논문지D
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• 제8D권4호
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• pp.347-360
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• 2001

공간 조인은 두 개의 데이터 집합으로부터 공간적인 조건을 만족하는 두 객체 쌍의 집합을 구하는 것으로 비용이 매우 큰 연산자이다. 지난 수년동안 공간 조인의 순차 수행 시간은 많이 향상되었지만, 그 응답시간은 사용자의 요구를 만족시키지 못하고 있다. 따라서 최근 병렬 시스템을 이용하여 이러한 문제를 해결하려는 연구가 진행되고 있다. 그렇지만 프로세서의 수가 증가할수록 병렬 처리에 의한 프로세서의 효율성은 급격히 떨어진다. 이것은 병렬 공간 조인을 수행할 경우 순차 공간 조인 보 다 디스크 병목 현상과 메시지 전송 오버헤드가 심하게 발생하기 때문이다. 이 논문에서는 공유 디스크 구조에서 다중 프로세서의 디스크 동시 접근으로 인한 병목 현상을 완화하고, 메시지 전송을 최소화하기 위한 태스크 할당 방법을 제안한다. 제안한 태스크 할당 방법을 두 가지 공간 조인 기법에 각각 적용하여 디스크 접근 횟수와 메시지 전송 횟수의 감소 효과를 실험으로 평가한다. MIMD 구조 및 공유디스크 방식의 병렬 시스템에서의 다양한 실험에서 이 논문에서 제안한 준동적 태스크 할당 방법이 정적 할당과 동적 할당 방법에 비해 우수함을 보였다.

• 한국정보과학회논문지:시스템및이론
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• 제33권9호
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• pp.699-708
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• 2006

버스 분할 기법은 통신이 많은 모듈들을 가까이 배치하고 필요한 버스 단편만 사용함으로 버스 에너지 소비를 줄인다. 그러나 MPSoC와 같은 다중 프로세서 플랫폼에서는 캐시 일관성을 유지하기 위하여 모든 프로세서에서 버스 트랜잭션을 알아야 하므로, 기존의 버스 분할 기법을 적용할 수 없다. 본 논문에서는 공유 메모리 기반의 MPSoC 플랫폼에서 버스 에너지를 절감시키기 위한 버스 분할 기법을 제안한다. 제안된 버스 분할 기법은 비 공유 메모리와 공유 메모리의 버스를 분할함으로써, 캐시 일관성을 유지하며 비 공유 메모리를 참조할 때 소비하는 버스 에너지를 최소화시킨다. 또한, 태스크별 버스 트랜잭션 횟수를 기반하여 태스크를 할당함으로써, 공유 메모리를 참조할 때 소비하는 버스 에너지를 절감시키는 캐시 일관성을 고려한 태스크 할당 기법을 제안한다. 시뮬레이션을 통한 실험에서 제안된 버스 분할 기법은 비 공유 메모리 참조시의 버스 에너지를 최대 83%까지 절감시키며, 태스크 할당 알고리즘은 공유 메모리 참조시의 버스 에너지를 최대 36%까지 절감시키는 효과가 있음을 보여준다. 그럼으로 다중 프로세서 시스템에서도 버스 분할 기법을 적용하여 버스 에너지 절감 효과를 볼 수 있으며, 캐시 일관성을 고려한 태스크 할당 기법을 통해 추가적으로 버스 에너지를 절감할 수 있음을 보여준다.

• 산업경영시스템학회지
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• 제22권50호
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• pp.23-32
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• 1999

Reliability and maintainability allocation in the analysis of the system's design, with the objective of planning and installing the individual components in such a way that the system performance is achieved. This paper has been made to solve an important task in reliability management of manufacturing systems within the general objective being to increase productivity while maintaining costs low. Thus, the purpose of this paper is to provide an analytical approach to determine an optimal reliability and maintainability allocation, trading off among system performance and parts investment costs. Two important considerations will be addressed in this regard : (ⅰ) determine the reliability and maintainability allocation of parts which maximizes a given production index, having fixed the total cost of investments ; and (ⅱ) determine the reliability and maintainability allocation which minimizes the total cost of investments, having fixed a minimum acceptable level of productivity. The procedure proposed in this paper is able to provide to managers and designers useful indications on the reliability and maintainability characteristics of parts in series -parallel systems. And this heuristic model is a decision support tool for contractors who are involved in large scale design projects such as ship and aircraft design. Numerical examples prove that an approximate expression of the average throughput rate is sufficiently accurate to be used in a numerical optimization method.

• Journal of Information Processing Systems
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• 제18권3호
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• pp.443-456
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• 2022

An efficient and reasonable resource allocation strategy can greatly improve the service quality of Internet of Vehicles (IoV). However, most of the current allocation methods have overestimation problem, and it is difficult to provide high-performance IoV network services. To solve this problem, this paper proposes a network resource allocation strategy based on deep learning network model DDQN. Firstly, the method implements the refined modeling of IoV model, including communication model, user layer computing model, edge layer offloading model, mobile model, etc., similar to the actual complex IoV application scenario. Then, the DDQN network model is used to calculate and solve the mathematical model of resource allocation. By decoupling the selection of target Q value action and the calculation of target Q value, the phenomenon of overestimation is avoided. It can provide higher-quality network services and ensure superior computing and processing performance in actual complex scenarios. Finally, simulation results show that the proposed method can maintain the network delay within 65 ms and show excellent network performance in high concurrency and complex scenes with task data volume of 500 kbits.

• 대한인간공학회지
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• 제32권1호
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• pp.59-68
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• 2013

Objective: The purpose of this paper is to introduce a task complexity model combining task design aspects and complexity dimensions and to explain an approach to identifying and organizing task complexity factors based on the model. Background: Task complexity is a critical concept in describing and predicting human performance in complex systems such as nuclear power plants(NPPs). In order to understand the nature of task complexity, task complexity factors need to be identified and organized in a systematic manner. Although several methods have been suggested for identifying and organizing task complexity factors, it is rare to find an analytical approach based on a theoretically sound model. Method: This study regarded a task as a system to be designed. Three levels of design ion, which are functional, behavioral, and structural level of a task, characterize the design aspects of a task. The behavioral aspect is further classified into five cognitive processing activity types(information collection, information analysis, decision and action selection, action implementation, and action feedback). The complexity dimensions describe a task complexity from different perspectives that are size, variety, and order/organization. Combining the design aspects and complexity dimensions of a task, we developed a model from which meaningful task complexity factors can be identified and organized in an analytic way. Results: A model consisting of two facets, each of which is respectively concerned with design aspects and complexity dimensions, were proposed. Additionally, twenty-one task complexity factors were identified and organized based on the model. Conclusion: The model and approach introduced in this paper can be effectively used for examining human performance and human-system interface design issues in NPPs. Application: The model and approach introduced in this paper could be used for several human factors problems, including task allocation and design of information aiding, in NPPs and extended to other types of complex systems such as air traffic control systems as well.

• Journal of Electrical Engineering and Technology
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• 제11권4호
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• pp.987-992
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• 2016

This study introduces an example environment where wireless devices are mobile, devices use dynamic voltage scaling, devices and tasks are heterogeneous, tasks have deadline, and the computation and communication power is dynamically changed for energy saving. For this type of environment, the efficient system-level energy management and resource management for task completion can be an essential part of the operation and design of such systems. Therefore, the resources are assigned to tasks and the tasks may be scheduled to maximize a goal which is to minimize energy usage while trying to complete as many tasks as possible by their deadlines. This paper also introduces mobility of nodes and variable transmission power for communication which complicates the resource management/task scheduling problem further.

• Journal of Electrical Engineering and Technology
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• 제4권3호
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• pp.337-345
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• 2009

Deregulation in power industry has made the reactive power ancillary service management a critical task to power system operators from both technical and economic perspectives. Reactive power management in power systems is a complex combinatorial optimization problem involving nonlinear functions with multiple local minima and nonlinear constraints. This paper proposes a practical market-based reactive power ancillary service management scheme to tackle the challenge. In this paper a new model for voltage security and reactive power management is presented. The proposed model minimizes reactive support cost as an economic aspect and insures the voltage security as a technical constraint. For modeling validation study, two optimization algorithm, a genetic algorithm (GA) and particle swarm optimization (PSO) method are used to solve the problem of optimum allocation of reactive power in power systems under open market environment and the results are compared. As a case study, the IEEE-30 bus power system is used. Results show that the algorithm is well competent for optimal allocation of reactive power under practical constraints and price based conditions.

• Journal of information and communication convergence engineering
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• 제9권2호
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• pp.155-160
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• 2011

In distributed source localization where sensors transmit measurements to a fusion node, we address the sensor selection problem where the goal is to find the best set of sensors that maximizes localization accuracy when quantization of sensor measurements is taken into account. Since sensor selection depends heavily upon rate assigned to each sensor, joint optimization of rate allocation and sensor selection is required to achieve the best solution. We show that this task could be accomplished by solving the problem of allocating rates to each sensor so as to minimize the error in estimating the position of a source. Then we solve this rate allocation problem by using the generalized BFOS algorithm. Our experiments demonstrate that the best set of sensors obtained from the proposed sensor selection algorithm leads to significant improvements in localization performance with respect to the set of sensors determined from a sensor selection process based on unquantized measurements.