• 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 Computing and Services
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• v.4 no.6
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• pp.13-24
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• 2003

Grid technology requires use of geographically distributed resources from multiple domains. Resource monitoring services or tools consisting sensors or agents will run on many systems to find static resource information (such as architecture vendor, OS name and version, MIPS rate, memory size, CPU capacity, disk size, and NIC information) and dynamic resource information (CPU usage, network usage(bandwidth, latency), memory usage, etc.). Thus monitoring itself may cause system overhead. This paper proposes the optimal monitoring interval to reduce the cost of monitoring services and the dynamic monitoring interval to measure monitoring events accurately. By employing two features, we find out unnecessary system overhead is significantly reduced and accuracy of events is still acquired.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1473-1473
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• 2003

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.6 no.1
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• pp.29-35
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• 2010

Long-term temperature monitoring has been performed for ground heat exchanger at the Earthquake Research Center (ERC) building in Korea Institute of Geoscience and Mineral Resources (KIGAM). For the 3 years of monitoring, overall temperature increases are observed at various depths within a borehole heat exchanger. But monitoring of ground temperature variation at the monitoring well beforehand showed that geothermal utilization is not the only source for the temperature increase, Because various kinds of sources can cause the ground temperature change, more thorough investigation should be followed.

• Journal of the Korea Society of Computer and Information
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• v.18 no.2
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• pp.41-47
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• 2013

In this paper, for this open system-based virtual resource monitoring system was designed. Virtual resources, CPU, memory, disk, network, each subdivided into parts, each modular implementation. Implementation results in real time CPU, memory, disk, network information, confirmed the results of monitoring. System designed to implement the Windows, Linux, Xen was used for the operating system, implementation language, C++ was used, the structure of the system, such as the ability to upgrade and add scalability and modularity by taking into account the features available in cloud computing environments applicable to cloud computing, virtual resource monitoring system has been implemented.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.95-100
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• 2022

Cloud computing platform is a shared pool of resources and services with various kind of models delivered to the customers through the Internet. The methods include an on-demand dynamically-scalable form charged using a pay-per-use model. The main problem with this model is the allocation of resource in dynamic. In this paper, we have proposed a mechanism to optimize the resource provisioning task by reducing the job completion time while, minimizing the associated cost. We present the Cooperative Agents Dynamic Resource Allocation and Monitoring in Cloud Computing CADRAM system, which includes more than one agent in order to manage and observe resource provided by the service provider while considering the Clients' quality of service (QoS) requirements as defined in the service-level agreement (SLA). Moreover, CADRAM contains a new Virtual Machine (VM) selection algorithm called the Node Failure Discovery (NFD) algorithm. The performance of the CADRAM system is evaluated using the CloudSim tool. The results illustrated that CADRAM system increases resource utilization and decreases power consumption while avoiding SLA violations.

• Journal of Korean Society for Quality Management
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• v.38 no.1
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• pp.64-74
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• 2010

Since management of information resources is getting more complicated in the distributed, heterogeneous computing environment, the capability of monitoring and controlling the dispersed information resources is perceived as a critical success factor for the effective enterprise-wide information resource management. Integrated Control Architecture(ICA) provides that capability. Utilizing such architecture, we can manage corporate information resources more efficiently, perform impact analysis for changes in information resources, and alleviate the human effort by automating the monitoring of critical information resources. In this paper, we propose a conceptual framework and metamodel of ICA.

• Journal of the Korean Solar Energy Society
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• v.31 no.6
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• pp.72-77
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• 2011

The purpose for installation of offshore weather station is a measurement of wind resources and so on. If weather station is operated, it will be possible to analysis for wind resource and arrangement of wind farm by using measured data. In this paper, we carried out the development of offshore wind resource measurement system for measuring offshore wind resource. Also, In order to monitor for real-time wind data with 1 Hz, we installed the wireless transmission system. All wind characteristic data are sent to the server PC through the this system is connected outport of DataLogger. Transmitted wind data were used in order to look at in the Web-page and tablet PC on a real time basis in a graph. In this paper, we will introduce about the wind resource measurement and remote monitoring system that is the result of study.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.2
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• pp.203-210
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• 2015

The ecological environment monitoring system configured with Sensor Node, Gateway, Service Platform, and Web Browser. In this paper, we designed gateway resource tree and service function to do handling in the ecological environment monitoring service. Gateway Service Function based on oneM2M Common Service Function, Gateway Resource Tree configured with Application Part handling Sensor Data and Gateway link handling. lastly Device Registration, Sensing, Control, Profile Management.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.5
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• pp.187-198
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• 2008

This paper develops a framework for efficient resource management within the grid service environment. Resource management is the core element of the grid service; therefore, GridRMF(Grid Resource Management Framework) is modeled and developed in order to respond to such variable characteristics of resources as accordingly as possible. GridRMF uses the participation level of grid resource as a basis of its hierarchical management. This hierarchical management divides managing domains into two parts: VMS(Virtual Organization Management System) for virtual organization management and RMS(Resource Management System) for metadata management. VMS mediates resources according to optimal virtual organization selection mechanism, and responds to malfunctions of the virtual organization by LRM(Local Resource Manager) automatic recovery mechanism. RMS, on the other hand, responds to load balance and fault by applying resource status monitoring information into adaptive performance-based task allocation algorithm.