• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.884-888
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• 2009

Vehicular Adhoc Networks (VANET), a Vehicle-to-Infrastucture or Vehicle-to-Vehicle communication technology, is an area that makes more specific use of Mobile Adhoc Networks(MANET). VANET's Quality of Service(QoS) focuses on preventing possible emergencies like car crash from happening by immediately transmitting information to the cars around, while MANET's QoS is being studied for the quality of multimedia data such as Video on Demand(VoD), Video streaming, Voice over IP(VoIP), etc. In this paper, I structure the actual network configuration using Link State Routing(LSR), implement QoS Provisioning Model using Common Open Policy Service(COPS), and suggest more effective k-hop Cluster and inter-domain policy negotiation which fit better to the characteristics of VANET.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.10
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• pp.1712-1732
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• 2011

Cloud provides dynamically scalable virtualized computing resources as a service over the Internet. To achieve higher resource utilization over virtualization technology, an optimized strategy that deploys virtual machines on physical machines is needed. That is, the total number of active physical host nodes should be dynamically changed to correspond to their resource usage rate, thereby maintaining optimum utilization of physical machines. In this paper, we propose a pattern-based prediction model for resource provisioning which facilitates best possible resource preparation by analyzing the resource utilization and deriving resource usage patterns. The focus of our work is on predicting future resource requests by optimized dynamic resource management strategy that is applied to a virtualized data center in a Cloud computing environment. To this end, we build a prediction model that is based on user request patterns and make a prediction of system behavior for the near future. As a result, this model can save time for predicting the needed resource amount and reduce the possibility of resource overuse. In addition, we studied the performance of our proposed model comparing with conventional resource provisioning models under various Cloud execution conditions. The experimental results showed that our pattern-based prediction model gives significant benefits over conventional models.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5286-5306
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• 2016

Emerging applications in automation, medical imaging, traffic monitoring and surveillance need real-time data transmission over Wireless Sensor Networks (WSNs). Guaranteeing Quality of Service (QoS) for real-time traffic over WSNs creates new challenges. Rapid penetration of smart devices, standardization of Machine Type Communications (MTC) in next generation 5G wireless networks have added new dimensions in these challenges. In order to satisfy such precise QoS constraints, in this paper, we propose a new cross-layer QoS-provisioning strategy in Wireless Multimedia Sensor Networks (WMSNs). The network layer performs statistical estimation of sensory QoS parameters. Identifying QoS-routing problem with multiple objectives as NP-complete, it discovers near-optimal QoS-routes by using evolutionary genetic algorithms. Subsequently, the Medium Access Control (MAC) layer classifies the packets, automatically adapts the contention window, based on QoS requirements and transmits the data by using routing information obtained by the network layer. Performance analysis is carried out to get an estimate of the overall system. Through the simulation results, it is manifested that the proposed strategy is able to achieve better throughput and significant lower delay, at the expense of negligible energy consumption, in comparison to existing WMSN QoS protocols.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1164-1183
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• 2019

The rapid development of cloud computing and high requirements of operators requires strong support from the underlying Data Center Networks. Therefore, the effectiveness of using resources in the data center networks becomes a point of concern for operators and material for research. In this paper, we discuss the online virtual-cluster provision problem for multiple tenants with an aim to decide when and where the virtual cluster should be placed in a data center network. Our objective is maximizing the total revenue for the data center networks under the constraints. In order to solve this problem, this paper divides it into two parts: online multi-tenancy scheduling and virtual cluster placement. The first part aims to determine the scheduling orders for the multiple tenants, and the second part aims to determine the locations of virtual machines. We first approach the problem by using the variational inequality model and discuss the existence of the optimal solution. After that, we prove that provisioning virtual clusters for a multi-tenant data center network that maximizes revenue is NP-hard. Due to the complexity of this problem, an efficient heuristic algorithm OMS (Online Multi-tenancy Scheduling) is proposed to solve the online multi-tenancy scheduling problem. We further explore the virtual cluster placement problem based on the OMS and propose a novel algorithm during the virtual machine placement. We evaluate our algorithms through a series of simulations, and the simulations results demonstrate that OMS can significantly increase the efficiency and total revenue for the data centers.

• Journal of the Korea Society for Simulation
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• v.20 no.4
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• pp.139-147
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• 2011

There is a growing tendency toward a vehicle demand and a utilization of traffic information systems. Due to various kinds of traffic information systems and increasing of communication data, the traffic information service requires a very high IT infrastructure. A cloud computing environment is an essential approach for reducing a IT infrastructure cost. And the traffic information service needs a provisioning scheduling method for managing a resource. So we propose a provisioning scheduling with conditional probability inference (PSCPI) for the traffic information service on cloud environment. PSCPI uses a naive bayse inference technique based on a status of a virtual machine. And PSCPI allocates a job to the virtual machines on the basis of an availability of each virtual machine. Naive bayse based PSCPI provides a high throughput and an high availability of virtual machines for real-time traffic information services.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1320-1329
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• 2022

Currently, advanced national research network groups are continuously conducting R&D for the requirement to provide SDN/NFV-based network automation and intelligence technology for R&E users. In addition, the requirement for providing large-scale data transmission with the high performance networking facility, compared to general network environments, is gradually increasing in the advanced national research networks. Accordingly, in this paper, we propose an open API-based virtual network provisioning automation platform for large data transmission researched and developed to respond to the networking requirements of the national research network and present the implementation results. The platform includes the KREONET-S VDN system that provides SDN-based network virtualization technology, and the Kubernetes system that provides container-oriented server virtualization technology, and the Globus Online, a high-performance data transmission system. In this paper, the environment configurations, the system implemetation results for the interworking between the heterogeneous systems, and the automated virtual network provisioning implementation results are presented.

• Journal of Forest and Environmental Science
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• v.33 no.2
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• pp.91-96
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• 2017

Trees at farm are considered as one of the option to reduce poverty of smallholders by contributing to livelihood security and resilience to climate change. A perception based study was conducted to assess the cultural importance of tree species suitable for practicing agroforestry in randomly selected agroforestry-dominated villages in Alaknanda valley of Western Himalayas during 2015-16. Semi-structured questionnaire was used to collect primary data on the provisioning services of major agroforestry tree species in randomly surveyed 87 households. Based on cultural importance (CI) index value, the most suitable agroforestry tree species was Morus alba (3.32) followed by Celtis australis (3.22), Mangifera indica (3.01), Grewia optiva (2.79), Toona ciliata (2.22), Bauhinia variegata (2.08), Leucaena leucocephala (1.76) and Emblica officinalis (1.74). The preference of use has also been governed based on their indigenous knowledge. This study will also facilitate in evaluating the importance of provisioning services of agroforestry tree species in improving livelihood as well as facilitates smallholder's resilience to climate change in Western Himalayas.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4720-4738
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• 2015

Proper management on user-driven virtual circuits (VCs) is essential for seamless operation of virtual networks. The Network Provisioning System (NPS) is useful software for creating user-driven VCs automatically and must take fault management into account for physical layer impairments on user-driven VCs. This paper addresses a user-driven and trusty protection management in an NPS with an open standard Network Service Interface (NSI), as a contribution to show how to implement the user-driven and trusty protection management required for user-driven VCs. In particular, it provides a RESTful web service Interface for Configuration and Event management (RICE) that enable management of a distinguished data and control plane VC status between Network Service Agents (NSAs) in the event of a node or link fault and repair in a domain. This capability represents a contribution to show how network and protection events in a domain can be monitored between NSAs (NPSs with the NSI) in multiple domains. The implemented NPS controls and manages both the primary and backup VC with disjoint path in a user-driven manner. A demonstration to verify RICE API's capability is addressed for the trusty protection in the dynamic VC network.

• Journal of Practical Engineering Education
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• v.10 no.2
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• pp.81-87
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• 2018

During the major sections of the network, Software-defined network control technology for the network area corresponding to the transmission network is becoming a change in network-controlled environments utilizing network operation and provisioning across the network industry. Currently development is underway along with the deployment of PTN equipment and configuration for provisioning is being phased out. It is actively introducing establishment of SDN-based control system while constructing provisioning of PTN equipment from actual commercial network. Therefore, in this thesis, we are going to look at the contents and trends of SDN systems in packet-based transmission networks based on PTN and use them in research on OpenDaylight, an open source for configuring SDN. It then Network Operator will study the software defined control techniques for operational education.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.1
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• pp.120-134
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• 2015

InVEST Water Yield model developed by Natural Capital Project was applied for South Korea to assess domestic forest ecosystem's water provisioning services. The InVEST Water Yield model required 8 input dataset, including six spatial map data and two derived by coefficients. By running the model with relatively easy acquired and modified data, the result of domestic forest ecosystem's water provisioning services was 9,409,622,083 ton using the standard of the year 2011. The result showed similar patterns and distribution of rainfall in 2011, but showed difference when compared with existing researches spatially driven in nationwide statistical analysis results. This difference is assumed to occur with different model mechanism in spatial implementation and statistical analysis. So given that the model is currently still developing, applications should be taken on qualitative perspectives rather than on quantitative perspectives. Additionally, for advancing the application of InVEST water yield model, quantification of suitable input data and comparison using multi-modeling is required.