• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.12
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• pp.2294-2314
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• 2011

The key issue in providing fast and reliable access on cloud services is the effective management of resources in a cloud system. However, the high variation in cloud service access rates affects the system performance considerably when there are no default routines to handle this type of occurrence. Adaptive techniques are used in resource management to support robust systems and maintain well-balanced loads within the servers. This paper presents an adaptive resource management for cloud systems which supports the integration of intelligent methods to promote quality of service (QoS) in provisioning of cloud services. A technique of dynamically assigning cloud services to a group of cloud servers is proposed for the adaptive resource management. Initially, cloud services are collected based on the excess cloud services load and then these are deployed to the assigned cloud servers. The assignment function uses the proposed proportional ordering which efficiently assigns cloud services based on its resource consumption. The difference in resource consumption rate in all nodes is analyzed periodically which decides the execution of service assignment. Performance evaluation showed that the proposed dynamic service assignment (DSA) performed best in throughput performance compared to other resource allocation algorithms.

• The KIPS Transactions:PartC
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• v.14C no.5
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• pp.453-462
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• 2007

NGN is a packet-based converged network to support session and non-session based services in QoS-enabled broadband transport technologies. Resource and admission control functions(RACF) of NGN have been considering COPS and SNMP as resource management protocols to collect network topology and resource status information of transport network. This paper defines requirements of resource management in NGN transport network, and proposes protocol independent information model to keep consistency of data models of each resource management protocol. Based on this information model described with UML class diagram, we designed and implemented NGN resource management system on Web Services.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5234-5251
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• 2018

It is well-known that virtualization technology can bring many benefits not only to users but also to service providers. From the view of system security and resource utility, higher resource sharing degree and higher system reliability can be obtained by the introduction of virtualization technology in distributed cloud. The small size time-sharing multiplexing technology which is based on virtual machine in distributed cloud platform can enhance the resource utilization effectively by server consolidation. In this paper, the concept of memory block and user satisfaction is redefined combined with user requirements. According to the unbalanced memory resource states and user preference requirements in multi-virtual machine environments, a model of proper memory resource allocation is proposed combined with memory block and user satisfaction, and at the same time a memory optimization allocation algorithm is proposed which is based on virtual memory block, makespan and user satisfaction under the premise of an orderly physical nodes states also. In the algorithm, a memory optimal problem can be transformed into a resource workload balance problem. All the virtual machine tasks are simulated in Cloudsim platform. And the experimental results show that the problem of virtual machine memory resource allocation can be solved flexibly and efficiently.

• The Korean Journal of Mycology
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• v.50 no.4
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• pp.347-355
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• 2022

A fungal isolate belonging to the phylum Ascomycota was isolated and identified as Talaromyces veerkampii in 2017 during a survey of fungal diversity in field soils in Korea. This fungal isolate was identified and described based on macro- and micromorphological and molecular characterization. The identification was also based on partial 18S-ITS1-5.8S-ITS2-28S rDNA and calmodulin (CaM)-encoding gene sequencing data. Talaromyces veerkampii has not been previously reported in Korea. Thus, we report here a newly discovered species from soil in Korea along with its morphological and molecular characteristics.

• Journal of the Korea Society for Simulation
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• v.23 no.4
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• pp.111-119
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• 2014

The cloud environment need resource management method that to enable the big data issue and data analysis technology. Existing resource management uses the limited calculation method, therefore concentrated the resource bias problem. To solve this problem, the resource management requires the learning-based scheduling using resource history information. In this paper, we proposes the ART (Adaptive Resonance Theory)-based adaptive resource management. Our proposed method assigns the job to the suitable method with the resource monitoring and history management in cloud computing environment. The proposed method utilizes the unsupervised learning method. Our goal is to improve the data processing and service stability with the adaptive resource management. The propose method allow the systematic management, and utilize the available resource efficiently.

• The KIPS Transactions:PartC
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• v.13C no.2 s.105
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• pp.227-234
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• 2006

In this paper, we propose a window based resource reservation scheme to minimize an waste bandwidth due to resource reservation in mobile networks. Specially, this scheme decides a proper timing to reserve resource by using the number of movement, which is provided by the differentiated handoff estimation model, among inner regions. In the previous resource reservation scheme[6], it requests a resource reservation to neighboring cells as soon as a mobile host enters or creates into a cell. But, after a proper time based on the number of movements in the differentiated handoff estimation model passes, the proposed scheme requests a resource reservation to neighboring cells. Because of this reason, it can improve resource utilization on mobile networks. And, this scheme differentiates resource reservation according to a request ratio for resource reservation to each neighboring cell. Also, this scheme improves resource reservation acceptance rate and bandwidth utilization.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.79-86
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• 2020

To make a satisfactory decision regarding project scheduling, a trade-off between the resource-related cost and project duration must be considered. A beneficial method for decision makers is to provide a number of alternative schedules of diverse project duration with minimum resource cost. In view of optimization, the alternative schedules are Pareto sets under multi-objective of project duration and resource cost. Assuming that resource cost is closely related to resource leveling, a heuristic algorithm for resource capacity reduction (HRCR) is developed in this study in order to generate the Pareto sets efficiently. The heuristic is based on the fact that resource leveling can be improved by systematically reducing the resource capacity. Once the reduced resource capacity is given, a schedule with minimum project duration can be obtained by solving a resource-constrained project scheduling problem. In HRCR, VNS (Variable Neighborhood Search) is implemented to solve the resource-constrained project scheduling problem. Extensive experiments to evaluate the HRCR performance are accomplished with standard benchmarking data sets, PSPLIB. Considering 5 resource leveling objective functions, it is shown that HRCR outperforms well-known multi-objective optimization algorithm, SPEA2 (Strength Pareto Evolutionary Algorithm-2), in generating dominant Pareto sets. The number of approximate Pareto optimal also can be extended by modifying weight parameter to reduce resource capacity in HRCR.

• Journal of the Korea Society for Simulation
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• v.16 no.2
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• pp.1-8
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• 2007

Resource management in grid computing environment is essential for integration and interaction among heterogeneous resources. This paper discusses resource management methods of centralized and decentralized broker-based modeling for solving complex problems of resource management and presents design and development of the decentralized broker-based resource management modeling in grid computing environment. This model comprises a global resource broker and a local resource broker, and we derive reduction of communication and functional dispersion of Job management using a local resource broker. The simulation experiment shows the improvement of resource utilization and average response time and proves that this model improves utilization of resources and replies to user requests promptly.

• Information Systems Review
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• v.10 no.3
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• pp.111-132
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• 2008

Although there are many processes in which factors interact with each other during enterprise resource planning(ERP) implementation, factors affecting ERP implementation have been investigated in an isolated way. In order to bridge the gap, this study attempts to provide a research model to explain how these factors affect ERP implementation success from a holistic perspective. In particular, this research focuses on how bundling and leveraging processes affect ERP implementation success using resource based theory, a strategy formulation framework, and a dynamic resource management model of value creation. The model amalgamates organizational resources and capabilities via the bundling and leveraging processes to identify the effect on ERP implementation success. This paper validates the proposed model by presenting Australian aviation industry case study. Case findings will be in help to reveal the effect of resource bundling in establishing capabilities and effect of capabilities leveraging in deriving the ERP implementation success.

• Journal of the Korea Society of Computer and Information
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• v.13 no.3
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• pp.169-177
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• 2008

Grid resources are composed of various communication networks and operation systems. When a grid system searches and selects grid resources, which meet requirements of a grid user, existing grid resource selection systems are limited due to their storage methods for resource information. In order to select grid resources suitable for requirements of a grid user and characteristics of data, this paper constructs an ontology for grid resources and proposes an ontology-based grid resource selection system. This system provides an inference engine based on rules defined by SWRL to create a resource list. Experimental results comparing the proposed system with existing grid resource selection systems, such as the Condor-G and the Nimrod-G, verify the effectiveness of the ontology-based grid resource selection system with improved job throughput and resource utilization and reduced job loss and job processing time.