• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.4776-4798
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• 2015

The location selection of virtual machines in distributed cloud is difficult because of the physical resource distribution, allocation of multi-dimensional resources, and resource unit cost. In this study, we propose a multi-object virtual machine location selection algorithm (MOVMLSA) based on group information, doubly linked list structure and genetic algorithm. On the basis of the collaboration of multi-dimensional resources, a fitness function is designed using fuzzy logic control parameters, which can be used to optimize search space solutions. In the location selection process, an orderly information code based on group and resource information can be generated by adopting the memory mechanism of biological immune systems. This approach, along with the dominant elite strategy, enables the updating of the population. The tournament selection method is used to optimize the operator mechanisms of the single-point crossover and X-point mutation during the population selection. Such a method can be used to obtain an optimal solution for the rapid location selection of virtual machines. Experimental results show that the proposed algorithm is effective in reducing the number of used physical machines and in improving the resource utilization of physical machines. The algorithm improves the utilization degree of multi-dimensional resource synergy and reduces the comprehensive unit cost of resources.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.195-204
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• 2003

Network optimization is being increasingly important and fundamental issue in the fields such as engineering, computer science, operations research, transportation, telecommunication, decision support systems, manufacturing, and airline scheduling. Networks provide a useful way to modeling real world problems and are extensively used in practice. Many real world applications impose on more complex issues, such as, complex structure, complex constraints, and multiple objects to be handled simultaneously and make the problem intractable to the traditional approaches. Recent advances in evolutionary computation have made it possible to solve such practical network optimization problems. The invited talk introduces a thorough treatment of evolutionary approaches, i.e., hybrid genetic algorithms approach to network optimization problems, such as, fixed charge transportation problem, minimum cost and maximum flow problem, minimum spanning tree problem, multiple project scheduling problems, scheduling problem in FMS.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.2
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• pp.1-8
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• 2003

The operation and management of a plant require proper accounting for the constraints coming from reliability requirements as well as from budget and resource considerations. Most of the mathematical methods to decide the inspection time interval for plant maintenance by reliability theory are too complicated to be solved. Moreover, the mathematical and theoretical models are not usually cases in the practical applications. In order to overcome these problems, we propose a new the decision-making method of optimal inspection interval to minimize the maintenance cost by reliability theory and genetic algorithm (GA). The most merit of the proposed method is to decide the inspection interval for a plant machine of which failure rate $\lambda$(t) conforms to any probability distribution. Therefore, this method is more practical. The efficiency of the proposed method is verified by comparing the results obtained by GA-based method with the inspection model haying regular time interval.

• Korean Journal of Ichthyology
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• v.21 no.sup1
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• pp.52-62
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• 2009

Environmental differences of each sea around the Korean Peninsula in terms of factors including topography and complexity of sea current may influence species and genetic diversity of marine fishes. Fish are naturally abundant in the frontal area where various currents or water masses meet. However, this food resource is prone to human overexploitation, threatening the marine ecosystem. New fisheries resources management strategies are needed. Such strategies require information about population structure obtained through morphological and genetic methods.

• Journal of the military operations research society of Korea
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• v.26 no.1
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• pp.56-69
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• 2000

A frequency assignment problem on time division duplex system is considered. Republic of Korea Army (ROKA) has been establishing an infrastructure of tactical communication (SPIDER) system for next generation and it will be a core network structure of system. VHF system is the backbone network of SPIDER, that performs transmission of data such as voice, text and images. So, it is a significant problem finding the frequency assignment with no interference under very restricted resource environment. With a given arbitrary configuration of communications network, we find a feasible solution that guarantees communication without interference between sites and relay stations. We formulate a frequency assignment problem as an Integer Programming model, which has NP-hard complexity. To find the assignment results within a reasonable time, we take a genetic algorithm approach which represents the solution structure with available frequency order, and develop a genetic operation strategies. Computational result shows that the network configuration of SPIDER can be solved efficiently within a very short time.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.11a
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• pp.592-601
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• 2007

In the conventional double auction approaches, two basic assumptions are usually applied - (1) each trader has a linear or quasi-linear utility function of price and quantity, (2) buyers as well as sellers have identical utility functions. However, in practice, these assumptions are unrealisitc. Therefore, a flexible and integrated double auction mechanism that can integrate all traders' diverse utility functions is necessary. We propose a double auction mechanism with resource allocation based on nonlinear utility functions, namely a flexible synchronous double auction system where each participant can express a diverse utility function on the price and quantity. In order to optimize the total market utility consists of multiple complex utility functions of traders, our study proposes a genetic algorithm (GA) We show the viability of the proposed mechanism through several simulation experiments.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.119-126
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• 2024

The volume of genomic data is constantly increasing in various modern industries and research fields. This growth presents new challenges and opportunities in terms of the quantity and diversity of genetic data. In this paper, we propose a distributed cloud system for integrating and managing large-scale gene databases. By introducing a distributed data storage and processing system based on the Hadoop Distributed File System (HDFS), various formats and sizes of genomic data can be efficiently integrated. Furthermore, by leveraging Spark on YARN, efficient management of distributed cloud computing tasks and optimal resource allocation are achieved. This establishes a foundation for the rapid processing and analysis of large-scale genomic data. Additionally, by utilizing BigQuery ML, machine learning models are developed to support genetic search and prediction, enabling researchers to more effectively utilize data. It is expected that this will contribute to driving innovative advancements in genetic research and applications.

• Parasites, Hosts and Diseases
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• v.51 no.6
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• pp.719-726
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• 2013

Mitochondrial genomes have been extensively studied for phylogenetic purposes and to investigate intra- and interspecific genetic variations. In recent years, numerous groups have undertaken sequencing of platyhelminth mitochondrial genomes. Haplorchis taichui (family Heterophyidae) is a trematode that infects humans and animals mainly in Asia, including the Mekong River basin. We sequenced and determined the organization of the complete mitochondrial genome of H. taichui. The mitochondrial genome is 15,130 bp long, containing 12 protein-coding genes, 2 ribosomal RNAs (rRNAs, a small and a large subunit), and 22 transfer RNAs (tRNAs). Like other trematodes, it does not encode the atp8 gene. All genes are transcribed from the same strand. The ATG initiation codon is used for 9 protein-coding genes, and GTG for the remaining 3 (nad1, nad4, and nad5). The mitochondrial genome of H. taichui has a single long non-coding region between trnE and trnG. H. taichui has evolved as being more closely related to Opisthorchiidae than other trematode groups with maximal support in the phylogenetic analysis. Our results could provide a resource for the comparative mitochondrial genome analysis of trematodes, and may yield genetic markers for molecular epidemiological investigations into intestinal flukes.

• Proceedings of the Korean Society of Plant Biotechnology Conference
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• 2005.11a
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• pp.187-187
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• 2005

• 대한예방의학회:학술대회논문집
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• 2004.10a
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• pp.52.1-52.1
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• 2004