• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2017.11a
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• pp.223-226
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• 2017

미디어의 생성 및 소비를 위한 기기의 다양화 및 소형화와 이로 인한 미디어 생성 및 소비의 패러다임이 변화함으로 인해, 이와 같은 시장의 요구사항에 부합하기 위한 다양한 기술의 개발 및 표준화가 가속화되고 있다. 이러한 시대의 변화에 발맞추어 국제 표준화 기구인 MPEG 은 네트워크 상에서의 다양한 미디어 간 시공간적 관계를 파악하고 관리하기 위한 표준인 Media Orchestration 표준화를 진행하였다. 이에 본 논문에서는 Media Orchestration 에서 제시한 미디어 간 공간적 Orchestration 구조를 기반으로 다양한 Metadata 를 이용하여 단말 및 미디어 간의 공간적 관계의 기술, 전달 및 소비 방안을 제시하였다.

• Journal of Communications and Networks
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• v.17 no.1
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• pp.67-74
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• 2015

In this paper, we propose a web-based content syndication system in which users can easily choose Internet protocol television (IPTV) contents. This system generates personalized content guide to provide a list of IPTV contents with respect to users' interests and statistics information of their online social community. For this, IPTV contents and relevant metadata are collected from various sources and transformed. Then, the service and content metadata are processed by user metadata including audience measurement and community metadata. The metadata flows are separated from content flows of transport network. The implementation of IPTV content syndication system demonstrates how to arrange IPTV contents efficiently from content providers to the end user's screen. We also show that the user metadata including online community information are important for the system's performance and the user's satisfaction.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.270-278
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• 2023

We propose a container orchestration system for process workloads that combines the potential of big data and machine learning technologies to integrate enterprise process-centric workloads. This proposed system analyzes big data generated from industrial automation to identify hidden patterns and build a machine learning prediction model. For each machine learning case, training data is loaded into a data store and preprocessed for model training. In the next step, you can use the training data to select and apply an appropriate model. Then evaluate the model using the following test data: This step is called model construction and can be performed in a deployment framework. Additionally, a visual hierarchy is constructed to display prediction results and facilitate big data analysis. In order to implement parallel computing of PCA in the proposed system, several virtual systems were implemented to build the cluster required for the big data cluster. The implementation for evaluation and analysis built the necessary clusters by creating multiple virtual machines in a big data cluster to implement parallel computation of PCA. The proposed system is modeled as layers of individual components that can be connected together. The advantage of a system is that components can be added, replaced, or reused without affecting the rest of the system.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.193-202
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• 2024

As companies specialize, they use more modern applications, but they still rely on legacy systems and data access is limited by data silos. In this paper, we propose the Fabricator system, a design system for metadata based on Data Fabric that plays a key role in the data orchestration layer consisting of three layers: Sources Engine, Workload Builder, and Data Fabric Ingestion, thereby achieving meaningful integration of data and information. Provides useful insights to users through conversion. This allows businesses to efficiently access and utilize data, overcoming the limitations of legacy systems.