• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.355-356
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• 2015

ICT 및 연구관리환경의 다변화와 발전방향에 비추어, 연구망을 효율적으로 운영관리하기 위한 시스템의 구현 및 운영환경을 NFV기반으로 구축하고, 발전하기 위한 NFVI 구성방안을 연구하고자 한다.

• Journal of Information Processing Systems
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• v.17 no.4
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• pp.801-817
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• 2021

Network virtualization technologies have played efficient roles in deploying cloud, Internet of Things (IoT), big data, and 5G network. We have conducted a survey on network virtualization technologies, such as software-defined networking (SDN), network functions virtualization (NFV), and network virtualization overlay (NVO). For each of technologies, we have explained the comprehensive architectures, applied technologies, and the advantages and disadvantages. Furthermore, this paper has provided a summarized view of the latest research works on challenges and solutions of security issues mainly focused on DDoS attack and encryption.

• TTA Journal
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• s.168
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• pp.76-81
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• 2016

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.6
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• pp.414-423
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• 2014

The number and size of resource constituting the web page has been increasing steadily, and this circumstance leads to rapidly falling quality of web service in mobile network that offer relatively higher delay. Moreover, Improving the quality of a web services protocol is difficult to provide network function because the current network architecture has closed structure. In this paper, we suggest schemes to enhance web performance in mobile network, which are Check Coded DOM scheme and Functional JavaScript Transmission scheme, and then try to seek idea which can be provided suggested schemes as a network function using NFV(Network Function Virtualization). For the performance evaluation and analysis about the suggested schemes, we perform network simulation using SMPL library. We confirm that suggested schemes offer better performance in term of page loading time, the number of message and the amount of traffic in the network than HTTP Protocol.

• KNOM Review
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• v.23 no.1
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• pp.34-42
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• 2020

Network Function Virtualization (NFV) environment can deal with dynamic changes in traffic status with appropriate deployment and scaling of Virtualized Network Function (VNF). However, determining and applying the optimal VNF deployment is a complicated and difficult task. In particular, it is necessary to predict the situation at a future point because it takes for the process to be applied and the deployment decision to the actual NFV environment. In this paper, we randomly generate service requests in Multiaccess Edge Computing (MEC) topology, then obtain training data for machine learning model from an Integer Linear Programming (ILP) solution. We use the simulation data to train the machine learning model which predicts the optimal VNF deployment in a predefined future point. The prediction model shows the accuracy over 90% compared to the ILP solution in a 5-minute future time point.

• KNOM Review
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• v.22 no.1
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• pp.1-10
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• 2019

The process to determine the required number of resources depends on the factors being considered. Autoscaling is one such mechanism that uses a wide range of factors to decide and is a critical process in NFV. As the networks are being shifted onto the cloud after the invention of SDN, we require better resource managers in the future. To solve this problem, we propose a solution that allows the VNFMs to autoscale the system resources depending on the factors such as overhead of hyperthreading, number of requests, execution-times for the virtual network functions. It is a known fact that the hyperthreaded virtual-cores are not fully capable of performing like the physical cores. Also, as there are different types of core having different frequencies so the process to calculate the number of cores needs to be measured accurately and precisely. The platform independency is achieved by proposing another solution in the form of a monitoring microservice, which communicates through APIs. Hence, by the use of our autoscaling application and a monitoring microservice, we enhance the resource provisioning process to meet the criteria of future networks.

• Convergence Security Journal
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• v.16 no.7
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• pp.3-11
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• 2016

With repid development of optical networking technology, Software-Defined Network (SDN) and Network Function Virtualization (NFV), high performance networking service, collaboration platform that enables collaborative research globally, drastically National Research Network (NRN) including Internet Service has changed. Therefore we compared and analyzed several world-class NRNs and took a view of future development strategy of the NRN. Also we suggest high speed security environment in super high bandwidth network with 40Gbps and 100Gbps optical transmission technology, network separation of NRN with Science DMZ to support high performance network transmission for science big data, building security environment for last-mile in campus network that supports programmability of IDS using BRO framework.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.4
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• pp.13-19
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• 2019

SDN is one of the most actively researched topics to solve traffic problems in communication. SDN implements multiple networks in a single physical network by virtualizing network resources through an advanced API. Network Function Virtualized (NFV) distributes network functions from hardware using software instant, virtualization technology to VNF. These features make network management easier and improve performance by virtualizing IP, routers, and so on. In this paper, we propose a method to control the traffic and provide the distributed controller effect of SDN through SDN distribution in the virtualized industrial network. It is expected that SDN distribution will be able to manage traffic more efficiently when using the proposed scheme.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.17-23
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• 2022

Network slicing is a promising paradigm and significant evolution for adjusting the heterogeneous services based on different requirements by placing dynamic virtual network functions (VNF) forwarding graph (VNFFG) and orchestrating service function chaining (SFC) based on criticalities of Quality of Service (QoS) classes. In system architecture, software-defined networks (SDN), network functions virtualization (NFV), and edge computing are used to provide resourceful data view, configurable virtual resources, and control interfaces for developing the modified deep reinforcement learning agent (MDRL-A). In this paper, task requests, tolerable delays, and required resources are differentiated for input state observations to identify the non-critical/critical classes, since each user equipment can execute different QoS application services. We design intelligent slicing for handing the cross-domain resource with MDRL-A in solving network problems and eliminating resource usage. The agent interacts with controllers and orchestrators to manage the flow rule installation and physical resource allocation in NFV infrastructure (NFVI) with the proposed formulation of completion time and criticality criteria. Simulation is conducted in SDN/NFV environment and capturing the QoS performances between conventional and MDRL-A approaches.

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.31 no.9
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• pp.8-13
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• 2013