• Proceedings of the IEEK Conference
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• 2000.11c
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• pp.9-12
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• 2000

Genetic algorithm is a searching method which based on the law of the survival of the fittest. Multi-population Genetic Algorithm is a modified form of Genetic Algorithm, which was devised for covering the defect of general genetic algorithm. The core of multi-population genetic algorithm is said to be the migration schemes. The fitness-based migration scheme and the random migration scheme are currently used. In this paper, a new migration scheme, ‘the migration scheme between groups’, is suggested, and compared to the general two migration schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.6
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• pp.1398-1417
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• 2013

A method is proposed to reduce excess resources from a virtual machine(VM) while avoiding subsequent migrations for a computer cluster that provides cloud service. The proposed scheme cuts down on the resources of a VM based on the probability that migration may occur after a reduction. First, it finds a VM that can be scaled down by analyzing the history of the resource usage. Then, the migration probability is calculated as a function of the VM resource usage trend and the trend error. Finally, the amount of resources needed to eliminate from an underutilized VM is determined such that the migration probability after the resource reduction is less than or equal to an acceptable migration probability. The acceptable migration probability, to be set by the cloud service provider, is a criterion to assign a weight to the resource reduction either to prevent VM migrations or to enhance VM utilization. The results of simulation show that the proposed scheme lowers migration frequency by 31.6~60.8% depending on the consistency of resource demand while losing VM utilization by 9.1~21.5% compared to other known approaches, such as the static and the prediction-based methods. It is also verified that the proposed scheme extends the elapsed time before the first occurrence of migration after resource reduction 1.1~2.3-fold. In addition, changes in migration frequency and VM utilization are analyzed with varying acceptable migration probabilities and the consistency of resource demand patterns. It is expected that the analysis results can help service providers choose a right value of the acceptable migration probability under various environments having different migration costs and operational costs.

• Journal of Information Processing Systems
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• v.11 no.1
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• pp.148-164
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• 2015

The use of mobile agents for collaborative processing in wireless sensor network has gained considerable attention. This is when mobile agents are used for data aggregation to exploit redundant and correlated data. The efficiency of agent-based data aggregation depends on the agent migration scheme. However, in general, most of the proposed schemes are centralized approach-based schemes where the sink node determines the migration paths for the agents before dispatching them in the sensor network. The main limitations with such schemes are that they need global network topology information for deriving the migration paths of the agents, which incurs additional communication overhead, since each node has a very limited communication range. In addition, a centralized approach does not provide fault tolerant and adaptive migration paths. In order to solve such problems, we have proposed a distributed approach-based scheme for determining the migration path of the agents where at each hop, the local information is used to decide the migration of the agents. In addition, we also propose a local repair mechanism for dealing with the faulty nodes. The simulation results show that the proposed scheme performs better than existing schemes in the presence of faulty nodes within the networks, and manages to report the aggregated data to the sink faster.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.80-83
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• 2003

A Genetic algorithm is a searching algorithm that based on the law of the survival of the fittest. Multi-population Genetic Algorithms are a modified form of genetic algorithm. Therefore, experience with fuzzy logic and genetic algorithm has proven to be that a combination of them can efficiently make up for their own deficiency. The Multi-population Genetic Algorithms independently evolve subpopulations. In this paper, we suggest a new coding method that independently evolves subpopulations using the fuzzy logic controller. The fuzzy logic controller has applied two fuzzy logic controllers that are implemented to adaptively adjust the crossover rate and mutation rate during the optimization process. The migration scheme in the multi-population genetic algorithms using fuzzy logic controllers is tested for a function optimization problem, and compared with other group migration schemes, therefore the groups migration scheme is then performed. The results demonstrate that the migration scheme in the multi-population genetic algorithms using fuzzy logic controller has a much better performance.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1480-1493
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• 2018

Recently, computational intelligence has received a lot of attention from researchers due to its potential applications to artificial intelligence. In computer science, computational intelligence refers to a machine's ability to learn how to compete various tasks, such as making observations or carrying out experiments. We adopted a computational intelligence solution to monitoring residual resources in cloud computing environments. The proposed residual resource monitoring scheme periodically monitors the cloud-based host machines, so that the post migration performance of a virtual machine is as consistent with the pre-migration performance as possible. To this end, we use a novel similarity measure to find the best target host to migrate a virtual machine to. The design of the proposed residual resource monitoring scheme helps maintain the quality of service and service level agreement during the migration. We carried out a number of experimental evaluations to demonstrate the effectiveness of the proposed residual resource monitoring scheme. Our results show that the proposed scheme intelligently measures the similarities between virtual machines in cloud computing environments without causing performance degradation, whilst preserving the quality of service and service level agreement.

• Journal of Internet of Things and Convergence
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• v.6 no.3
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• pp.39-44
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• 2020

In this paper, we propose a SDN-based fog computing service mobility support scheme. Fog computing architecture has been attracted because it enables task offloading services to IoT(Internet of Things) devices which has limited computing and power resources. However, since static as well as mobile IoT devices are candidate service targets for the fog computing service, the efficient task offloading scheme considering the mobility should be required. Especially for the IoT services which need low-latency response, the new connection and task offloading delay with the new fog computing node after handover can occur QoS(Quality of Service) degradation. Therefore, this paper proposes an efficient service mobility support scheme which considers both task migration and flow rule pre-installations. Task migration allows for the service connectivity when the fog computing node needs to be changed. In addition, the flow rule pre-installations into the forwarding nodes along the path after handover enables to reduce the connection delay and service interruption time.

• The Journal of Korean Association of Computer Education
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• v.12 no.4
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• pp.47-55
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• 2009

There are many researches considering mobile devices as resources in mobile grids. However, the mobile device has some limitations: wireless connection and battery capacity. So, the grid operations using mobile devices have lower reliability and efficiency than those in fixed grid environments. In this paper, we propose a job migration scheme using mobile devices to overcome these limitations. The proposed job migration scheme predicts failure condition during execution and takes checkpoints. Then, if the failure occurs on mobile device during execution, the executing job can be migrated to other mobile device by checkpoint information. To perform the proposed migration scheme, we establish a mobile device manager on a proxy server and a status manager on a mobile device. Connection, wireless signal strength and battery capacity of mobile devices are identified through two managers. The simulation results show improvement of efficiency and reliability during execution.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.14-15
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• 2007

Now-a-days, data and task migration in collaborative work provides enormous facilities to users. Here, we propose an ontology-based information management scheme to facilitate data and task migration in collaborative work. This ontologybased model will help us to organize huge information (e.g. device status, runtime state etc.) efficiently.

• 한국전산유체공학회:학술대회논문집
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• 2010.05a
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• pp.556-561
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• 2010

This paper proposes a three-dimensional haptotaxis model to simulate the migration of the population of cancer cells. The invasion of the cancer cells relates with the hapto- and the effect of the energy between cells and (ECM). The diffuse interface model is employed, which incorporates haptotaxis mechanism and interface energies. The semi-implicit Fourier spectral scheme is adopted for efficient complications. The simulation results reveal rich dynamics of cancer cells migration.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.1662-1665
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• 2010

그린 컴퓨팅의 일환으로 데이터 센터(Data Center)의 전력 효율을 고려한 소프트웨어/하드웨어 기술연구가 활발하게 진행되고 있다. 데이터 센터에서는 부하 분산(Load Balancing) 서비스의 마이그레이션(Migration) 기법을 통해 서비스의 품질을 높이고 데이터 센터의 효율성을 극대화 시킨다. 본 논문에서는 데이터 센터에서 냉각으로 소모되는 전력 절감을 위해 데이터 센터의 환경과 시스템 부하(Work Load)량에 기반을 둔 프로세스 마이그레이션(Process Migration) 기법을 제안한다.