• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1525-1530
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• 2021

By applying AI-based efficient inventory management and logistics optimization technology using the smart factory's production plan and manufacturing data, the company's productivity improvement and customer satisfaction can be expected to increase. In this paper, we proposed a system that collects data from the factory's production process, stores it in the cloud, and uses the manufacturing data stored there to apply AI-based supply chain optimization technology later. While the existing system supported approximately 10 to 20 data types, the proposed system is designed and developed to support more than 100 data types. In addition, in the case of the collection cycle, data can be collected 1-2 times per second, and data collection in TB units is possible. Therefore This system is designed to be applied to the existing factory of past in addition to the smart factory.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.6
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• pp.7-20
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• 2017

The advancement of cloud and big data and the considerable growth of traffic have increased the complexity and problems in the management inefficiency of existing networks. The software-defined networking (SDN) environment has been developed to solve this problem. SDN enables us to control network equipment through programming by separating the transmission and control functions of the equipment. Accordingly, several studies have been conducted to improve the performance of SDN controllers, such as the method of connecting existing legacy equipment with SDN, the packet management method for efficient data communication, and the method of distributing controller load in a centralized architecture. However, there is insufficient research on the control of SDN in terms of the quality of network-using applications. To support the establishment and change of the routing paths that meet the required network service quality, we require a mechanism to identify network requirements based on a contract for application network service quality and to collect information about the current network status and identify the violations of network service quality. This study proposes a method of identifying the quality violations of network paths through ontology to ensure the network service quality of applications and provide efficient services in an SDN environment.