• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.206-215
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• 2005

In this paper, we propose a new design method of Genetic Algorithm Processor(GAP) and Evolvable Hardware(EHW). All sorts of creature evolve its structure or shape in order to adapt itself to environments. Evolutionary Computation based on the process of natural selection not only searches the quasi-optimal solution through the evolution process, but also changes the structure to get best results. On the other hand, Genetic Algorithm(GA) is good fur finding solutions of complex optimization problems. However, it has a major drawback, which is its slow execution speed when is implemented in software of a conventional computer. Parallel processing has been one approach to overcome the speed problem of GA. In a point of view of GA, long bit string length caused the system of GA to spend much time that clear up the problem. Evolvable Hardware refers to the automation of electronic circuit design through artificial evolution, and is currently increased with the interested topic in a research domain and an engineering methodology. The studies of EHW generally use the XC6200 of Xilinx. The structure of XC6200 can configure with gate unit. Each unit has connected up, down, right and left cell. But the products can't use because had sterilized. So this paper uses Vertex-E (XCV2000E). The cell of FPGA is made up of Configuration Logic Block (CLB) and can't reconfigure with gate unit. This paper uses Vertex-E is composed of the component as cell of XC6200 cell in VertexE

• The Journal of Korean Association of Computer Education
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• v.9 no.1
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• pp.107-118
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• 2006

Load redistribution algorithm is a critical factor in computer system. In a receiver-initiated load redistribution algorithm, receiver(underloaded processor) continues to send unnecessary request messages for load transfer until a sender(overloaded processor) is found while the system load is light. Therefore, it yields many problems such as low cpu utilization and system throughput because of inefficient inter-processor communications until the receiver receives an accept message from the sender in this environment. This paper presents an approach based on genetic algorithm(GA) for dynamic load redistribution including self-adjustable in heterogeneous distributed systems. In this scheme the processors to which the requests are sent off are determined by the proposed GA to decrease unnecessary request messages.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.6 no.6
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• pp.506-512
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• 2005

Load redistribution algorithm is a critical factor in computer system. In a receiver-initiated Toad redistribution algorithm, receiver(underloaded processor) continues to send unnecessary request messages for load transfer until a sender(overloaded processor) is found while the system load is light. Therefore, it yields many problems such as low cpu utilization and system throughput because of inefficient inter-processor communications until the receiver receives an accept message from the sender in this environment. This paper presents an approach based on genetic algorithm(GA) for dynamic load redistribution including self-adjustable in heterogeneous distributed systems. In this scheme the processors to which the requests are sent off are determined by the proposed GA to decrease unnecessary request messages.

• The Journal of the Korea Contents Association
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• v.5 no.3
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• pp.183-191
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• 2005

In a sender-initiated load sharing algorithms, sender(overloaded processor) continues to send unnecessary request messages for load transfer until receiver(underloaded processor) is found while the system load is heavy. Therefore, it yields many problems such as low CPU utilization and system throughput because of inefficient inter-processor communications until the sender receives an accept message from the receiver in this environment. This paper presents an approach based on genetic algorithm(GA) for dynamic load sharing in heterogeneous distributed systems. In this scheme the processors to which the requests are sent off is determined by the proposed GA to decrease unnecessary request messages.

• The KIPS Transactions:PartA
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• v.10A no.1
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• pp.49-58
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• 2003

In a sender-initiated load balancing algorithm, a sender (overloaded processor) continues to send unnecessary request messages for load transfer until a receiver (underloaded processor) is found while the system load is heavy. Therefore, it yields many problems such as low cpu utilization and system throughput because of inefficient inter-processor communications until the sender receives an accept message from the receiver in this environment. This paper presents an approach based on genetic algorithm (GA) for dynamic load balancing in heterogeneous distributed systems. In this scheme the processors to which the requests are sent off are determined by the proposed GA to decrease unnecessary request messages.

• Journal of the Korea Society of Computer and Information
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• v.11 no.1 s.39
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• pp.1-10
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• 2006

Load redistribution algorithm is a critical factor in computer system. In a receiver-initiated load redistribution algorithm, receiver(underloaded processor) continues to send unnecessary request messages for load transfer until a sender(overloaded processor) is found while the system load is light. Therefore, it yields many problems such as low CPU utilization and system throughput because of inefficient inter-processor communications until the receiver receives an accept message from the sender in this environment. This paper presents an approach based on genetic. algorithm(GA) for dynamic load redistribution in heterogeneous distributed systems. In this scheme the processors to which the requests are sent off are determined by the proposed GA to decrease unnecessary request messages.

• Journal of Internet Computing and Services
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• v.5 no.6
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• pp.93-101
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• 2004

In a receiver-initiated load redistribution algorithm, receiver(underloaded processor) continues to send unnecessary request messages for load transfer until a sender(overloaded processor) is found while the system load is light, Therefore, it yields many problems such as low cpu utilization and system throughput because of inefficient inter-processor communications until the receiver receives an accept message from the sender in this environment. This paper presents an approach based on genetic algorithm(GA) for dynamic load redistribution in heterogeneous distributed systems. In this scheme the processors to which the requests are sent off are determined by the proposed GA to decrease unnecessary request messages. The performance of proposed algorithm shows better than that of the conventional algorithm through various experiments.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.2
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• pp.15-27
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• 1998

In the parallel processing systems, a compiler partitions a loaded program into tasks, allocates the tasks on multiple processors and schedules the tasks on each allocated processor. In this paper we suggest a Genetic Algorithm(GA) based scheduling method to find an optimal allocation and sequence of tasks on each Processor. The suggested method uses a chromosome which consists of task sequence and binary string that represent the number and order of tasks on each processor respectively. Two correction algorithms are used to maintain precedency constraints of the tasks in the chromosome. This scheduling method determines the optimal number of processors within limited numbers, and then finds the optimal schedule for each processor. A result from computational experiment of the suggested method is given.

• Journal of KIISE:Software and Applications
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• v.31 no.10
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• pp.1345-1355
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• 2004

In a sender-initiated load redistribution algorithm, a sender(overloaded processor) continues to send unnecessary request messages for load transfer until a receiver(underloaded processor) is found while the system load is heavy. In a receiver-initiated load redistribution algorithm, a receiver continues to send unnecessary request messages for load acquisition until a sender is found while the system load is light. Therefore, it yields many problems such as low CPU utilization and system throughput because of inefficient inter-processor communications in this environment. This paper presents an approach based on genetic algorithm(GA) for adaptive load sharing in distributed systems. In this scheme, the processors to which the requests are sent off are determined by the proposed GA to decrease unnecessary request messages.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.11a
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• pp.539-542
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• 2004

The $ZnGa_2O_4$ phosphor target is synthesized through solid-state reactions at the calcine temperature of $700^{\circ}C$ and sintering temperature of $1300^{\circ}C$ in order to deposit $ZnGa_2O_4$ phosphor thin film by rf magnetron sputtering system. The $ZnGa_2O_4$ phosphor thin film is deposited on Si(100) substrate and prepared $ZnGa_2O_4$ phosphor thin film is annealed by rapid thermal processor(RTP) at $700^{\circ}C$, 15sec. The x-ray diffraction patterns of $ZnGa_2O_4$ phosphor target and thin film show the position of (311) main peak. The cathodoluminescenre(CL) spectrums of $ZnGa_2O_4$ phosphor thin film show main peak of 420nm and maximum intensity at the substrate temperature of $500^{\circ}C$ and annealing temperature of $700^{\circ}C$ 15sec.